Overview

Dataset statistics

Number of variables103
Number of observations56127
Missing cells300480
Missing cells (%)5.2%
Total size in memory44.1 MiB
Average record size in memory824.0 B

Variable types

Numeric94
Text9

Alerts

Assists - away has 8909 (15.9%) missing valuesMissing
Assists - home has 8909 (15.9%) missing valuesMissing
Ball Safe - away has 7211 (12.8%) missing valuesMissing
Ball Safe - home has 7211 (12.8%) missing valuesMissing
Counter Attacks - away has 28066 (50.0%) missing valuesMissing
Counter Attacks - home has 28066 (50.0%) missing valuesMissing
Free Kicks - away has 51070 (91.0%) missing valuesMissing
Free Kicks - home has 51070 (91.0%) missing valuesMissing
Goal Attempts - away has 8229 (14.7%) missing valuesMissing
Goal Attempts - home has 8229 (14.7%) missing valuesMissing
Headers - away has 4262 (7.6%) missing valuesMissing
Headers - home has 4262 (7.6%) missing valuesMissing
Injuries - away has 25464 (45.4%) missing valuesMissing
Injuries - home has 25464 (45.4%) missing valuesMissing
Long Passes - away has 2010 (3.6%) missing valuesMissing
Long Passes - home has 2010 (3.6%) missing valuesMissing
Offsides - away has 2823 (5.0%) missing valuesMissing
Offsides - home has 2823 (5.0%) missing valuesMissing
Successful Headers - away has 4262 (7.6%) missing valuesMissing
Successful Headers - home has 4262 (7.6%) missing valuesMissing
Yellowred Cards - away has 7128 (12.7%) missing valuesMissing
Yellowred Cards - home has 7128 (12.7%) missing valuesMissing
second has 1027 (1.8%) zerosZeros
Accurate Crosses - away has 16977 (30.2%) zerosZeros
Accurate Crosses - home has 12876 (22.9%) zerosZeros
Assists - away has 25245 (45.0%) zerosZeros
Assists - home has 23444 (41.8%) zerosZeros
Attacks - away has 787 (1.4%) zerosZeros
Attacks - home has 711 (1.3%) zerosZeros
Ball Safe - away has 747 (1.3%) zerosZeros
Ball Safe - home has 753 (1.3%) zerosZeros
Challenges - away has 6821 (12.2%) zerosZeros
Challenges - home has 6550 (11.7%) zerosZeros
Corners - away has 15936 (28.4%) zerosZeros
Corners - home has 14481 (25.8%) zerosZeros
Counter Attacks - away has 13033 (23.2%) zerosZeros
Counter Attacks - home has 11294 (20.1%) zerosZeros
Dangerous Attacks - away has 2721 (4.8%) zerosZeros
Dangerous Attacks - home has 2239 (4.0%) zerosZeros
Dribble Attempts - away has 3014 (5.4%) zerosZeros
Dribble Attempts - home has 3100 (5.5%) zerosZeros
Fouls - away has 2913 (5.2%) zerosZeros
Fouls - home has 3228 (5.8%) zerosZeros
Goal Attempts - away has 9912 (17.7%) zerosZeros
Goal Attempts - home has 7117 (12.7%) zerosZeros
Goal Kicks - away has 8009 (14.3%) zerosZeros
Goal Kicks - home has 9116 (16.2%) zerosZeros
Goals - away has 32441 (57.8%) zerosZeros
Goals - home has 30960 (55.2%) zerosZeros
Headers - away has 2989 (5.3%) zerosZeros
Headers - home has 2864 (5.1%) zerosZeros
Hit Woodwork - away has 49363 (87.9%) zerosZeros
Hit Woodwork - home has 48713 (86.8%) zerosZeros
Injuries - away has 15353 (27.4%) zerosZeros
Injuries - home has 17556 (31.3%) zerosZeros
Interceptions - away has 6592 (11.7%) zerosZeros
Interceptions - home has 6304 (11.2%) zerosZeros
Key Passes - away has 9347 (16.7%) zerosZeros
Key Passes - home has 7224 (12.9%) zerosZeros
Long Passes - away has 3086 (5.5%) zerosZeros
Long Passes - home has 3013 (5.4%) zerosZeros
Offsides - away has 23853 (42.5%) zerosZeros
Offsides - home has 20980 (37.4%) zerosZeros
Passes - home has 590 (1.1%) zerosZeros
Penalties - away has 52712 (93.9%) zerosZeros
Penalties - home has 51789 (92.3%) zerosZeros
Redcards - away has 54472 (97.1%) zerosZeros
Redcards - home has 54439 (97.0%) zerosZeros
Saves - away has 14816 (26.4%) zerosZeros
Saves - home has 20188 (36.0%) zerosZeros
Score Change - away has 55491 (98.9%) zerosZeros
Score Change - home has 55401 (98.7%) zerosZeros
Shots Blocked - away has 20782 (37.0%) zerosZeros
Shots Blocked - home has 18750 (33.4%) zerosZeros
Shots Insidebox - away has 11801 (21.0%) zerosZeros
Shots Insidebox - home has 9526 (17.0%) zerosZeros
Shots Off Target - away has 15584 (27.8%) zerosZeros
Shots Off Target - home has 13281 (23.7%) zerosZeros
Shots On Target - away has 17076 (30.4%) zerosZeros
Shots On Target - home has 13824 (24.6%) zerosZeros
Shots Outsidebox - away has 17391 (31.0%) zerosZeros
Shots Outsidebox - home has 15508 (27.6%) zerosZeros
Shots Total - away has 7911 (14.1%) zerosZeros
Shots Total - home has 6497 (11.6%) zerosZeros
Substitutions - away has 34436 (61.4%) zerosZeros
Substitutions - home has 35474 (63.2%) zerosZeros
Successful Dribbles - away has 10187 (18.1%) zerosZeros
Successful Dribbles - home has 9851 (17.6%) zerosZeros
Successful Headers - away has 5087 (9.1%) zerosZeros
Successful Headers - home has 5236 (9.3%) zerosZeros
Successful Interceptions - away has 3730 (6.6%) zerosZeros
Successful Interceptions - home has 3843 (6.8%) zerosZeros
Successful Passes - away has 602 (1.1%) zerosZeros
Successful Passes - home has 645 (1.1%) zerosZeros
Successful Passes Percentage - home has 637 (1.1%) zerosZeros
Tackles - away has 3493 (6.2%) zerosZeros
Tackles - home has 3513 (6.3%) zerosZeros
Throwins - away has 3394 (6.0%) zerosZeros
Throwins - home has 2862 (5.1%) zerosZeros
Total Crosses - away has 5430 (9.7%) zerosZeros
Total Crosses - home has 4129 (7.4%) zerosZeros
Yellowcards - away has 28723 (51.2%) zerosZeros
Yellowcards - home has 30840 (54.9%) zerosZeros
Yellowred Cards - away has 48597 (86.6%) zerosZeros
Yellowred Cards - home has 48763 (86.9%) zerosZeros

Reproduction

Analysis started2025-01-04 15:11:49.073566
Analysis finished2025-01-04 15:11:50.844875
Duration1.77 second
Software versionydata-profiling vv4.7.0
Download configurationconfig.json

Variables

fixture_id
Real number (ℝ)

Distinct648
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19147822.91
Minimum19134453
Maximum19172117
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:51.149959image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum19134453
5-th percentile19134484
Q119135296
median19139734
Q319155124
95-th percentile19172084
Maximum19172117
Range37664
Interquartile range (IQR)19828

Descriptive statistics

Standard deviation13434.62878
Coefficient of variation (CV)0.0007016269601
Kurtosis-0.9700580048
Mean19147822.91
Median Absolute Deviation (MAD)5266
Skewness0.6056266584
Sum1.074709856 × 1012
Variance180489250.4
MonotonicityIncreasing
2025-01-04T15:11:51.317951image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19139727 105
 
0.2%
19135296 105
 
0.2%
19134489 104
 
0.2%
19139737 103
 
0.2%
19135275 102
 
0.2%
19135255 102
 
0.2%
19135264 102
 
0.2%
19134525 101
 
0.2%
19135314 101
 
0.2%
19154584 101
 
0.2%
Other values (638) 55101
98.2%
ValueCountFrequency (%)
19134453 94
0.2%
19134454 87
0.2%
19134455 82
0.1%
19134456 83
0.1%
19134457 97
0.2%
ValueCountFrequency (%)
19172117 78
0.1%
19172116 90
0.2%
19172115 89
0.2%
19172114 89
0.2%
19172113 92
0.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:51.471682image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters449016
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1st-half
2nd row1st-half
3rd row1st-half
4th row1st-half
5th row1st-half
ValueCountFrequency (%)
1st-half 29148
51.9%
2nd-half 26979
48.1%
2025-01-04T15:11:51.707479image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 56127
12.5%
h 56127
12.5%
a 56127
12.5%
l 56127
12.5%
f 56127
12.5%
1 29148
6.5%
s 29148
6.5%
t 29148
6.5%
2 26979
6.0%
n 26979
6.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 449016
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
- 56127
12.5%
h 56127
12.5%
a 56127
12.5%
l 56127
12.5%
f 56127
12.5%
1 29148
6.5%
s 29148
6.5%
t 29148
6.5%
2 26979
6.0%
n 26979
6.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 449016
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
- 56127
12.5%
h 56127
12.5%
a 56127
12.5%
l 56127
12.5%
f 56127
12.5%
1 29148
6.5%
s 29148
6.5%
t 29148
6.5%
2 26979
6.0%
n 26979
6.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 449016
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
- 56127
12.5%
h 56127
12.5%
a 56127
12.5%
l 56127
12.5%
f 56127
12.5%
1 29148
6.5%
s 29148
6.5%
t 29148
6.5%
2 26979
6.0%
n 26979
6.0%
Distinct31342
Distinct (%)55.8%
Missing0
Missing (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:51.918884image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1066413
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17386 ?
Unique (%)31.0%

Sample

1st row2024-08-16 19:01:19
2nd row2024-08-16 19:02:18
3rd row2024-08-16 19:03:19
4th row2024-08-16 19:04:18
5th row2024-08-16 19:05:19
ValueCountFrequency (%)
2024-08-31 2491
 
2.2%
2024-10-05 2400
 
2.1%
2024-09-14 2386
 
2.1%
2024-08-24 2335
 
2.1%
2024-11-10 2309
 
2.1%
2024-09-28 2297
 
2.0%
2024-10-06 2172
 
1.9%
2024-09-21 2166
 
1.9%
2024-11-02 2128
 
1.9%
2024-11-09 2068
 
1.8%
Other values (3075) 89502
79.7%
2025-01-04T15:11:52.262990image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 178281
16.7%
2 165814
15.5%
0 145377
13.6%
- 112254
10.5%
: 112254
10.5%
4 105462
9.9%
8 57901
 
5.4%
56127
 
5.3%
9 43456
 
4.1%
5 27163
 
2.5%
Other values (3) 62324
 
5.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1066413
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 178281
16.7%
2 165814
15.5%
0 145377
13.6%
- 112254
10.5%
: 112254
10.5%
4 105462
9.9%
8 57901
 
5.4%
56127
 
5.3%
9 43456
 
4.1%
5 27163
 
2.5%
Other values (3) 62324
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1066413
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 178281
16.7%
2 165814
15.5%
0 145377
13.6%
- 112254
10.5%
: 112254
10.5%
4 105462
9.9%
8 57901
 
5.4%
56127
 
5.3%
9 43456
 
4.1%
5 27163
 
2.5%
Other values (3) 62324
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1066413
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 178281
16.7%
2 165814
15.5%
0 145377
13.6%
- 112254
10.5%
: 112254
10.5%
4 105462
9.9%
8 57901
 
5.4%
56127
 
5.3%
9 43456
 
4.1%
5 27163
 
2.5%
Other values (3) 62324
 
5.8%
Distinct1271
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:52.589128image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1066413
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2024-08-16 19:00:31
2nd row2024-08-16 19:00:31
3rd row2024-08-16 19:00:31
4th row2024-08-16 19:00:31
5th row2024-08-16 19:00:31
ValueCountFrequency (%)
2024-08-31 2491
 
2.2%
2024-10-05 2400
 
2.1%
2024-09-14 2386
 
2.1%
2024-08-24 2335
 
2.1%
2024-11-10 2309
 
2.1%
2024-09-28 2297
 
2.0%
2024-10-06 2172
 
1.9%
2024-09-21 2166
 
1.9%
2024-11-02 2128
 
1.9%
2024-11-09 2068
 
1.8%
Other values (1193) 89502
79.7%
2025-01-04T15:11:53.043704image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 186502
17.5%
2 165925
15.6%
1 139324
13.1%
- 112254
10.5%
: 112254
10.5%
4 93652
8.8%
56127
 
5.3%
3 47647
 
4.5%
9 39273
 
3.7%
5 34968
 
3.3%
Other values (3) 78487
7.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1066413
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 186502
17.5%
2 165925
15.6%
1 139324
13.1%
- 112254
10.5%
: 112254
10.5%
4 93652
8.8%
56127
 
5.3%
3 47647
 
4.5%
9 39273
 
3.7%
5 34968
 
3.3%
Other values (3) 78487
7.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1066413
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 186502
17.5%
2 165925
15.6%
1 139324
13.1%
- 112254
10.5%
: 112254
10.5%
4 93652
8.8%
56127
 
5.3%
3 47647
 
4.5%
9 39273
 
3.7%
5 34968
 
3.3%
Other values (3) 78487
7.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1066413
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 186502
17.5%
2 165925
15.6%
1 139324
13.1%
- 112254
10.5%
: 112254
10.5%
4 93652
8.8%
56127
 
5.3%
3 47647
 
4.5%
9 39273
 
3.7%
5 34968
 
3.3%
Other values (3) 78487
7.4%
Distinct638
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:53.367596image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1066413
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-08-16 19:00:31
2nd row2024-08-16 19:00:31
3rd row2024-08-16 19:00:31
4th row2024-08-16 19:00:31
5th row2024-08-16 19:00:31
ValueCountFrequency (%)
2024-08-31 2491
 
2.2%
2024-10-05 2400
 
2.1%
2024-09-14 2386
 
2.1%
2024-08-24 2335
 
2.1%
2024-11-10 2309
 
2.1%
2024-09-28 2297
 
2.0%
2024-10-06 2172
 
1.9%
2024-09-21 2166
 
1.9%
2024-11-02 2128
 
1.9%
2024-11-09 2068
 
1.8%
Other values (582) 89502
79.7%
2025-01-04T15:11:53.808923image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 198857
18.6%
2 159711
15.0%
1 148161
13.9%
- 112254
10.5%
: 112254
10.5%
4 91684
8.6%
56127
 
5.3%
3 46930
 
4.4%
9 38152
 
3.6%
8 32271
 
3.0%
Other values (3) 70012
 
6.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1066413
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 198857
18.6%
2 159711
15.0%
1 148161
13.9%
- 112254
10.5%
: 112254
10.5%
4 91684
8.6%
56127
 
5.3%
3 46930
 
4.4%
9 38152
 
3.6%
8 32271
 
3.0%
Other values (3) 70012
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1066413
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 198857
18.6%
2 159711
15.0%
1 148161
13.9%
- 112254
10.5%
: 112254
10.5%
4 91684
8.6%
56127
 
5.3%
3 46930
 
4.4%
9 38152
 
3.6%
8 32271
 
3.0%
Other values (3) 70012
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1066413
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 198857
18.6%
2 159711
15.0%
1 148161
13.9%
- 112254
10.5%
: 112254
10.5%
4 91684
8.6%
56127
 
5.3%
3 46930
 
4.4%
9 38152
 
3.6%
8 32271
 
3.0%
Other values (3) 70012
 
6.6%

minute
Real number (ℝ)

Distinct79
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.31311134
Minimum0
Maximum80
Zeros226
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:53.984791image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q112
median24
Q336
95-th percentile46
Maximum80
Range80
Interquartile range (IQR)24

Descriptive statistics

Standard deviation14.03480015
Coefficient of variation (CV)0.5772523292
Kurtosis-1.106720954
Mean24.31311134
Median Absolute Deviation (MAD)12
Skewness0.07275831073
Sum1364622
Variance196.9756152
MonotonicityNot monotonic
2025-01-04T15:11:54.147614image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 1215
 
2.2%
11 1206
 
2.1%
7 1205
 
2.1%
9 1204
 
2.1%
4 1201
 
2.1%
14 1193
 
2.1%
17 1193
 
2.1%
3 1193
 
2.1%
8 1193
 
2.1%
10 1193
 
2.1%
Other values (69) 44131
78.6%
ValueCountFrequency (%)
0 226
 
0.4%
1 1004
1.8%
2 1182
2.1%
3 1193
2.1%
4 1201
2.1%
ValueCountFrequency (%)
80 1
< 0.1%
79 1
< 0.1%
78 1
< 0.1%
77 1
< 0.1%
76 1
< 0.1%

second
Real number (ℝ)

ZEROS 

Distinct60
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.7120459
Minimum0
Maximum59
Zeros1027
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:54.309168image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q110
median27
Q344
95-th percentile56
Maximum59
Range59
Interquartile range (IQR)34

Descriptive statistics

Standard deviation18.30550101
Coefficient of variation (CV)0.6605611539
Kurtosis-1.351797631
Mean27.7120459
Median Absolute Deviation (MAD)17
Skewness0.1496097921
Sum1555394
Variance335.0913674
MonotonicityNot monotonic
2025-01-04T15:11:54.467860image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7 2001
 
3.6%
9 1864
 
3.3%
10 1678
 
3.0%
11 1484
 
2.6%
5 1467
 
2.6%
12 1435
 
2.6%
53 1369
 
2.4%
6 1362
 
2.4%
4 1258
 
2.2%
8 1189
 
2.1%
Other values (50) 41020
73.1%
ValueCountFrequency (%)
0 1027
1.8%
1 1103
2.0%
2 875
1.6%
3 787
1.4%
4 1258
2.2%
ValueCountFrequency (%)
59 1050
1.9%
58 817
1.5%
57 773
1.4%
56 1143
2.0%
55 1109
2.0%
Distinct49078
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:54.701607image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1066413
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43055 ?
Unique (%)76.7%

Sample

1st row2024-08-16 19:01:17
2nd row2024-08-16 19:02:16
3rd row2024-08-16 19:03:15
4th row2024-08-16 19:04:08
5th row2024-08-16 19:05:15
ValueCountFrequency (%)
2024-08-31 2491
 
2.2%
2024-10-05 2400
 
2.1%
2024-09-14 2386
 
2.1%
2024-08-24 2335
 
2.1%
2024-11-10 2309
 
2.1%
2024-09-28 2297
 
2.0%
2024-10-06 2172
 
1.9%
2024-09-21 2166
 
1.9%
2024-11-02 2128
 
1.9%
2024-11-09 2068
 
1.8%
Other values (15701) 89502
79.7%
2025-01-04T15:11:55.055997image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 167417
15.7%
0 159196
14.9%
1 149785
14.0%
- 112254
10.5%
: 112254
10.5%
4 94079
8.8%
56127
 
5.3%
3 45277
 
4.2%
9 42291
 
4.0%
5 37412
 
3.5%
Other values (3) 90321
8.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1066413
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 167417
15.7%
0 159196
14.9%
1 149785
14.0%
- 112254
10.5%
: 112254
10.5%
4 94079
8.8%
56127
 
5.3%
3 45277
 
4.2%
9 42291
 
4.0%
5 37412
 
3.5%
Other values (3) 90321
8.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1066413
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 167417
15.7%
0 159196
14.9%
1 149785
14.0%
- 112254
10.5%
: 112254
10.5%
4 94079
8.8%
56127
 
5.3%
3 45277
 
4.2%
9 42291
 
4.0%
5 37412
 
3.5%
Other values (3) 90321
8.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1066413
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 167417
15.7%
0 159196
14.9%
1 149785
14.0%
- 112254
10.5%
: 112254
10.5%
4 94079
8.8%
56127
 
5.3%
3 45277
 
4.2%
9 42291
 
4.0%
5 37412
 
3.5%
Other values (3) 90321
8.5%

1
Real number (ℝ)

Distinct120
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.38430203
Minimum1
Maximum501
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:55.224965image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.02
Q11.4
median2.5
Q35
95-th percentile51
Maximum501
Range500
Interquartile range (IQR)3.6

Descriptive statistics

Standard deviation44.4601169
Coefficient of variation (CV)3.590038163
Kurtosis69.84039313
Mean12.38430203
Median Absolute Deviation (MAD)1.3
Skewness7.811918367
Sum695093.72
Variance1976.701995
MonotonicityNot monotonic
2025-01-04T15:11:55.380839image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1334
 
2.4%
2.75 1148
 
2.0%
4 1130
 
2.0%
2.5 1095
 
2.0%
3.75 989
 
1.8%
2.87 979
 
1.7%
2.2 960
 
1.7%
5 928
 
1.7%
4.33 925
 
1.6%
5.5 915
 
1.6%
Other values (110) 45724
81.5%
ValueCountFrequency (%)
1 1334
2.4%
1.01 770
1.4%
1.02 783
1.4%
1.03 554
1.0%
1.04 534
1.0%
ValueCountFrequency (%)
501 162
0.3%
451 61
 
0.1%
401 81
0.1%
351 92
0.2%
301 126
0.2%

2
Real number (ℝ)

Distinct111
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.37175335
Minimum1
Maximum501
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:55.534897image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.06
Q12
median4
Q311
95-th percentile81
Maximum501
Range500
Interquartile range (IQR)9

Descriptive statistics

Standard deviation60.1366539
Coefficient of variation (CV)2.951962596
Kurtosis37.2343808
Mean20.37175335
Median Absolute Deviation (MAD)2.56
Skewness5.807883356
Sum1143405.4
Variance3616.417142
MonotonicityNot monotonic
2025-01-04T15:11:55.691946image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 1409
 
2.5%
5.5 1403
 
2.5%
41 1374
 
2.4%
4 1313
 
2.3%
51 1279
 
2.3%
5 1267
 
2.3%
3.75 1187
 
2.1%
4.33 1088
 
1.9%
15 1080
 
1.9%
6.5 1024
 
1.8%
Other values (101) 43703
77.9%
ValueCountFrequency (%)
1 748
1.3%
1.01 529
0.9%
1.02 416
0.7%
1.03 389
0.7%
1.04 308
0.5%
ValueCountFrequency (%)
501 342
0.6%
451 107
 
0.2%
401 155
0.3%
351 178
0.3%
301 238
0.4%

X
Real number (ℝ)

Distinct96
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.543399612
Minimum1
Maximum51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:55.844106image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.57
Q12.87
median3.6
Q36
95-th percentile23
Maximum51
Range50
Interquartile range (IQR)3.13

Descriptive statistics

Standard deviation8.274892272
Coefficient of variation (CV)1.264616677
Kurtosis13.0709667
Mean6.543399612
Median Absolute Deviation (MAD)1.15
Skewness3.451330376
Sum367261.39
Variance68.47384211
MonotonicityNot monotonic
2025-01-04T15:11:56.001614image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 2812
 
5.0%
3.75 2465
 
4.4%
3.4 2453
 
4.4%
3.25 2186
 
3.9%
3 1954
 
3.5%
3.6 1947
 
3.5%
3.1 1946
 
3.5%
2.87 1823
 
3.2%
4.33 1816
 
3.2%
3.5 1806
 
3.2%
Other values (86) 34919
62.2%
ValueCountFrequency (%)
1 1
 
< 0.1%
1.01 13
 
< 0.1%
1.02 53
0.1%
1.03 69
0.1%
1.04 77
0.1%
ValueCountFrequency (%)
51 724
1.3%
41 785
1.4%
34 44
 
0.1%
29 307
 
0.5%
26 653
1.2%

name
Text

Distinct648
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:56.270653image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length49
Median length37
Mean length25.10880681
Min length12

Characters and Unicode

Total characters1409282
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowManchester United vs Fulham
2nd rowManchester United vs Fulham
3rd rowManchester United vs Fulham
4th rowManchester United vs Fulham
5th rowManchester United vs Fulham
ValueCountFrequency (%)
vs 56127
 
24.8%
real 4343
 
1.9%
fc 3466
 
1.5%
united 2920
 
1.3%
madrid 2181
 
1.0%
city 2039
 
0.9%
manchester 2002
 
0.9%
olympique 1856
 
0.8%
borussia 1757
 
0.8%
vfl 1697
 
0.7%
Other values (153) 148100
65.4%
2025-01-04T15:11:56.729930image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
170361
 
12.1%
s 115079
 
8.2%
a 113553
 
8.1%
e 107699
 
7.6%
o 74926
 
5.3%
r 74396
 
5.3%
n 74004
 
5.3%
i 68756
 
4.9%
v 67324
 
4.8%
l 63994
 
4.5%
Other values (54) 479190
34.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1409282
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
170361
 
12.1%
s 115079
 
8.2%
a 113553
 
8.1%
e 107699
 
7.6%
o 74926
 
5.3%
r 74396
 
5.3%
n 74004
 
5.3%
i 68756
 
4.9%
v 67324
 
4.8%
l 63994
 
4.5%
Other values (54) 479190
34.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1409282
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
170361
 
12.1%
s 115079
 
8.2%
a 113553
 
8.1%
e 107699
 
7.6%
o 74926
 
5.3%
r 74396
 
5.3%
n 74004
 
5.3%
i 68756
 
4.9%
v 67324
 
4.8%
l 63994
 
4.5%
Other values (54) 479190
34.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1409282
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
170361
 
12.1%
s 115079
 
8.2%
a 113553
 
8.1%
e 107699
 
7.6%
o 74926
 
5.3%
r 74396
 
5.3%
n 74004
 
5.3%
i 68756
 
4.9%
v 67324
 
4.8%
l 63994
 
4.5%
Other values (54) 479190
34.0%

Accurate Crosses - away
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.830919165
Minimum0
Maximum12
Zeros16977
Zeros (%)30.2%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:56.875332image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile6
Maximum12
Range12
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.910672276
Coefficient of variation (CV)1.043559056
Kurtosis2.077084393
Mean1.830919165
Median Absolute Deviation (MAD)1
Skewness1.343840913
Sum102764
Variance3.650668547
MonotonicityNot monotonic
2025-01-04T15:11:57.002810image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 16977
30.2%
1 12945
23.1%
2 9867
17.6%
3 6664
 
11.9%
4 4263
 
7.6%
5 2413
 
4.3%
6 1545
 
2.8%
7 643
 
1.1%
8 388
 
0.7%
9 203
 
0.4%
Other values (3) 219
 
0.4%
ValueCountFrequency (%)
0 16977
30.2%
1 12945
23.1%
2 9867
17.6%
3 6664
 
11.9%
4 4263
 
7.6%
ValueCountFrequency (%)
12 31
 
0.1%
11 22
 
< 0.1%
10 166
0.3%
9 203
0.4%
8 388
0.7%

Accurate Crosses - home
Real number (ℝ)

ZEROS 

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.381687958
Minimum0
Maximum13
Zeros12876
Zeros (%)22.9%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:57.124644image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile7
Maximum13
Range13
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.237000436
Coefficient of variation (CV)0.9392500093
Kurtosis1.520985449
Mean2.381687958
Median Absolute Deviation (MAD)1
Skewness1.174224128
Sum133677
Variance5.004170953
MonotonicityNot monotonic
2025-01-04T15:11:57.251414image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 12876
22.9%
1 11223
20.0%
2 9809
17.5%
3 7445
13.3%
4 5535
9.9%
5 3829
 
6.8%
6 2332
 
4.2%
7 1387
 
2.5%
8 758
 
1.4%
9 354
 
0.6%
Other values (4) 579
 
1.0%
ValueCountFrequency (%)
0 12876
22.9%
1 11223
20.0%
2 9809
17.5%
3 7445
13.3%
4 5535
9.9%
ValueCountFrequency (%)
13 59
 
0.1%
12 81
 
0.1%
11 136
 
0.2%
10 303
0.5%
9 354
0.6%

Assists - away
Real number (ℝ)

MISSING  ZEROS 

Distinct5
Distinct (%)< 0.1%
Missing8909
Missing (%)15.9%
Infinite0
Infinite (%)0.0%
Mean0.5587699606
Minimum0
Maximum4
Zeros25245
Zeros (%)45.0%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:57.365442image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.6753790372
Coefficient of variation (CV)1.208688879
Kurtosis0.7845075253
Mean0.5587699606
Median Absolute Deviation (MAD)0
Skewness1.032973206
Sum26384
Variance0.4561368439
MonotonicityNot monotonic
2025-01-04T15:11:57.487023image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
0 25245
45.0%
1 18087
32.2%
2 3373
 
6.0%
3 501
 
0.9%
4 12
 
< 0.1%
(Missing) 8909
 
15.9%
ValueCountFrequency (%)
0 25245
45.0%
1 18087
32.2%
2 3373
 
6.0%
3 501
 
0.9%
4 12
 
< 0.1%
ValueCountFrequency (%)
4 12
 
< 0.1%
3 501
 
0.9%
2 3373
 
6.0%
1 18087
32.2%
0 25245
45.0%

Assists - home
Real number (ℝ)

MISSING  ZEROS 

Distinct4
Distinct (%)< 0.1%
Missing8909
Missing (%)15.9%
Infinite0
Infinite (%)0.0%
Mean0.6127747893
Minimum0
Maximum3
Zeros23444
Zeros (%)41.8%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:57.600154image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile2
Maximum3
Range3
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.6972662901
Coefficient of variation (CV)1.137883448
Kurtosis0.6558874951
Mean0.6127747893
Median Absolute Deviation (MAD)1
Skewness0.9634638368
Sum28934
Variance0.4861802793
MonotonicityNot monotonic
2025-01-04T15:11:57.705215image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
0 23444
41.8%
1 19330
34.4%
2 3728
 
6.6%
3 716
 
1.3%
(Missing) 8909
 
15.9%
ValueCountFrequency (%)
0 23444
41.8%
1 19330
34.4%
2 3728
 
6.6%
3 716
 
1.3%
ValueCountFrequency (%)
3 716
 
1.3%
2 3728
 
6.6%
1 19330
34.4%
0 23444
41.8%

Attacks - away
Real number (ℝ)

ZEROS 

Distinct168
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.45534235
Minimum0
Maximum170
Zeros787
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:58.034021image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q120
median41
Q363
95-th percentile93
Maximum170
Range170
Interquartile range (IQR)43

Descriptive statistics

Standard deviation28.46925942
Coefficient of variation (CV)0.655138307
Kurtosis-0.2543225275
Mean43.45534235
Median Absolute Deviation (MAD)22
Skewness0.5121735064
Sum2439018
Variance810.4987317
MonotonicityNot monotonic
2025-01-04T15:11:58.191323image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 787
 
1.4%
31 758
 
1.4%
5 741
 
1.3%
12 739
 
1.3%
16 738
 
1.3%
8 738
 
1.3%
6 730
 
1.3%
7 725
 
1.3%
57 721
 
1.3%
26 721
 
1.3%
Other values (158) 48729
86.8%
ValueCountFrequency (%)
0 787
1.4%
1 624
1.1%
2 620
1.1%
3 625
1.1%
4 644
1.1%
ValueCountFrequency (%)
170 1
 
< 0.1%
168 1
 
< 0.1%
166 1
 
< 0.1%
165 10
< 0.1%
164 1
 
< 0.1%

Attacks - home
Real number (ℝ)

ZEROS 

Distinct172
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48.22962211
Minimum0
Maximum174
Zeros711
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:58.348397image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q122
median45
Q370
95-th percentile104
Maximum174
Range174
Interquartile range (IQR)48

Descriptive statistics

Standard deviation31.49436058
Coefficient of variation (CV)0.6530086532
Kurtosis-0.3590282128
Mean48.22962211
Median Absolute Deviation (MAD)24
Skewness0.4900985229
Sum2706984
Variance991.8947481
MonotonicityNot monotonic
2025-01-04T15:11:58.512452image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 711
 
1.3%
17 694
 
1.2%
4 689
 
1.2%
46 670
 
1.2%
9 667
 
1.2%
7 666
 
1.2%
12 663
 
1.2%
19 662
 
1.2%
6 644
 
1.1%
36 634
 
1.1%
Other values (162) 49427
88.1%
ValueCountFrequency (%)
0 711
1.3%
1 491
0.9%
2 580
1.0%
3 615
1.1%
4 689
1.2%
ValueCountFrequency (%)
174 1
 
< 0.1%
173 1
 
< 0.1%
171 3
< 0.1%
169 5
< 0.1%
168 1
 
< 0.1%

Ball Possession % - away
Real number (ℝ)

Distinct98
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.11627203
Minimum0
Maximum100
Zeros302
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:58.676737image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile27
Q139
median49
Q359
95-th percentile72
Maximum100
Range100
Interquartile range (IQR)20

Descriptive statistics

Standard deviation14.54708205
Coefficient of variation (CV)0.296176429
Kurtosis0.8054633939
Mean49.11627203
Median Absolute Deviation (MAD)10
Skewness0.1141094256
Sum2756749
Variance211.6175963
MonotonicityNot monotonic
2025-01-04T15:11:58.838234image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50 1946
 
3.5%
52 1660
 
3.0%
48 1651
 
2.9%
46 1650
 
2.9%
49 1581
 
2.8%
53 1578
 
2.8%
51 1540
 
2.7%
54 1495
 
2.7%
47 1475
 
2.6%
44 1438
 
2.6%
Other values (88) 40113
71.5%
ValueCountFrequency (%)
0 302
0.5%
2 7
 
< 0.1%
3 2
 
< 0.1%
4 2
 
< 0.1%
6 10
 
< 0.1%
ValueCountFrequency (%)
100 367
0.7%
98 3
 
< 0.1%
97 1
 
< 0.1%
96 7
 
< 0.1%
95 2
 
< 0.1%

Ball Possession % - home
Real number (ℝ)

Distinct98
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.88260552
Minimum0
Maximum100
Zeros369
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:58.999327image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile28
Q141
median51
Q361
95-th percentile73
Maximum100
Range100
Interquartile range (IQR)20

Descriptive statistics

Standard deviation14.55366028
Coefficient of variation (CV)0.2860242736
Kurtosis0.8064680051
Mean50.88260552
Median Absolute Deviation (MAD)10
Skewness-0.1151813306
Sum2855888
Variance211.8090277
MonotonicityNot monotonic
2025-01-04T15:11:59.159471image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50 1933
 
3.4%
48 1664
 
3.0%
52 1654
 
2.9%
54 1644
 
2.9%
51 1589
 
2.8%
47 1574
 
2.8%
49 1539
 
2.7%
46 1497
 
2.7%
53 1476
 
2.6%
56 1440
 
2.6%
Other values (88) 40117
71.5%
ValueCountFrequency (%)
0 369
0.7%
2 3
 
< 0.1%
3 1
 
< 0.1%
4 7
 
< 0.1%
5 2
 
< 0.1%
ValueCountFrequency (%)
100 302
0.5%
98 7
 
< 0.1%
97 2
 
< 0.1%
96 2
 
< 0.1%
94 10
 
< 0.1%

Ball Safe - away
Real number (ℝ)

MISSING  ZEROS 

Distinct108
Distinct (%)0.2%
Missing7211
Missing (%)12.8%
Infinite0
Infinite (%)0.0%
Mean26.94588683
Minimum0
Maximum123
Zeros747
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:59.316394image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q110
median24
Q341
95-th percentile62
Maximum123
Range123
Interquartile range (IQR)31

Descriptive statistics

Standard deviation19.78716445
Coefficient of variation (CV)0.73432968
Kurtosis-0.1008926703
Mean26.94588683
Median Absolute Deviation (MAD)15
Skewness0.6673799081
Sum1318085
Variance391.531877
MonotonicityNot monotonic
2025-01-04T15:11:59.480213image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 1554
 
2.8%
9 1456
 
2.6%
1 1423
 
2.5%
7 1385
 
2.5%
4 1373
 
2.4%
5 1175
 
2.1%
2 1112
 
2.0%
19 1019
 
1.8%
16 1000
 
1.8%
27 983
 
1.8%
Other values (98) 36436
64.9%
(Missing) 7211
 
12.8%
ValueCountFrequency (%)
0 747
1.3%
1 1423
2.5%
2 1112
2.0%
3 1554
2.8%
4 1373
2.4%
ValueCountFrequency (%)
123 9
< 0.1%
117 10
< 0.1%
116 2
 
< 0.1%
106 3
 
< 0.1%
103 14
< 0.1%

Ball Safe - home
Real number (ℝ)

MISSING  ZEROS 

Distinct104
Distinct (%)0.2%
Missing7211
Missing (%)12.8%
Infinite0
Infinite (%)0.0%
Mean25.88741925
Minimum0
Maximum120
Zeros753
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:59.641870image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q19
median23
Q339
95-th percentile62
Maximum120
Range120
Interquartile range (IQR)30

Descriptive statistics

Standard deviation19.32038872
Coefficient of variation (CV)0.7463234761
Kurtosis0.08872558465
Mean25.88741925
Median Absolute Deviation (MAD)15
Skewness0.7388695653
Sum1266309
Variance373.2774204
MonotonicityNot monotonic
2025-01-04T15:11:59.800379image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1589
 
2.8%
6 1541
 
2.7%
4 1520
 
2.7%
5 1356
 
2.4%
2 1310
 
2.3%
8 1219
 
2.2%
10 1156
 
2.1%
33 1136
 
2.0%
7 1117
 
2.0%
17 1051
 
1.9%
Other values (94) 35921
64.0%
(Missing) 7211
 
12.8%
ValueCountFrequency (%)
0 753
1.3%
1 1589
2.8%
2 1310
2.3%
3 1041
1.9%
4 1520
2.7%
ValueCountFrequency (%)
120 7
 
< 0.1%
111 3
 
< 0.1%
106 19
< 0.1%
103 1
 
< 0.1%
100 27
< 0.1%

Challenges - away
Real number (ℝ)

ZEROS 

Distinct22
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.035312773
Minimum0
Maximum21
Zeros6821
Zeros (%)12.2%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:11:59.938084image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q36
95-th percentile10
Maximum21
Range21
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.205406723
Coefficient of variation (CV)0.7943391016
Kurtosis0.5280041215
Mean4.035312773
Median Absolute Deviation (MAD)2
Skewness0.8666035258
Sum226490
Variance10.27463226
MonotonicityNot monotonic
2025-01-04T15:12:00.059566image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 7665
13.7%
2 7207
12.8%
0 6821
12.2%
3 6498
11.6%
4 5856
10.4%
5 5685
10.1%
6 4610
8.2%
7 3650
6.5%
8 2602
 
4.6%
9 1763
 
3.1%
Other values (12) 3770
6.7%
ValueCountFrequency (%)
0 6821
12.2%
1 7665
13.7%
2 7207
12.8%
3 6498
11.6%
4 5856
10.4%
ValueCountFrequency (%)
21 4
 
< 0.1%
20 4
 
< 0.1%
19 11
 
< 0.1%
18 8
 
< 0.1%
17 40
0.1%

Challenges - home
Real number (ℝ)

ZEROS 

Distinct23
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.995153848
Minimum0
Maximum22
Zeros6550
Zeros (%)11.7%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:00.180601image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q36
95-th percentile10
Maximum22
Range22
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.277975193
Coefficient of variation (CV)0.8204878506
Kurtosis1.097990697
Mean3.995153848
Median Absolute Deviation (MAD)2
Skewness1.027790588
Sum224236
Variance10.74512137
MonotonicityNot monotonic
2025-01-04T15:12:00.302631image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 8578
15.3%
2 7157
12.8%
3 6844
12.2%
0 6550
11.7%
4 5877
10.5%
5 5645
10.1%
6 3908
7.0%
7 3229
 
5.8%
8 2539
 
4.5%
9 1834
 
3.3%
Other values (13) 3966
7.1%
ValueCountFrequency (%)
0 6550
11.7%
1 8578
15.3%
2 7157
12.8%
3 6844
12.2%
4 5877
10.5%
ValueCountFrequency (%)
22 3
 
< 0.1%
21 22
< 0.1%
20 22
< 0.1%
19 8
 
< 0.1%
18 28
< 0.1%

Corners - away
Real number (ℝ)

ZEROS 

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.030484437
Minimum0
Maximum17
Zeros15936
Zeros (%)28.4%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:00.417861image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile6
Maximum17
Range17
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.088212673
Coefficient of variation (CV)1.02843077
Kurtosis2.42318861
Mean2.030484437
Median Absolute Deviation (MAD)1
Skewness1.388563381
Sum113965
Variance4.360632169
MonotonicityNot monotonic
2025-01-04T15:12:00.545122image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 15936
28.4%
1 11604
20.7%
2 10628
18.9%
3 6429
11.5%
4 4588
 
8.2%
5 3013
 
5.4%
6 1807
 
3.2%
7 903
 
1.6%
8 521
 
0.9%
9 307
 
0.5%
Other values (7) 391
 
0.7%
ValueCountFrequency (%)
0 15936
28.4%
1 11604
20.7%
2 10628
18.9%
3 6429
11.5%
4 4588
 
8.2%
ValueCountFrequency (%)
17 1
 
< 0.1%
15 2
 
< 0.1%
14 4
 
< 0.1%
13 37
0.1%
12 70
0.1%

Corners - home
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.488855631
Minimum0
Maximum17
Zeros14481
Zeros (%)25.8%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:00.672335image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q34
95-th percentile7
Maximum17
Range17
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.452451216
Coefficient of variation (CV)0.9853730305
Kurtosis1.633615864
Mean2.488855631
Median Absolute Deviation (MAD)2
Skewness1.210771445
Sum139692
Variance6.014516965
MonotonicityNot monotonic
2025-01-04T15:12:00.802052image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 14481
25.8%
1 9938
17.7%
2 8251
14.7%
3 7750
13.8%
4 5029
 
9.0%
5 3692
 
6.6%
6 3023
 
5.4%
7 1473
 
2.6%
8 1220
 
2.2%
9 478
 
0.9%
Other values (8) 792
 
1.4%
ValueCountFrequency (%)
0 14481
25.8%
1 9938
17.7%
2 8251
14.7%
3 7750
13.8%
4 5029
 
9.0%
ValueCountFrequency (%)
17 5
 
< 0.1%
16 15
 
< 0.1%
15 13
 
< 0.1%
14 21
 
< 0.1%
13 71
0.1%

Counter Attacks - away
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)< 0.1%
Missing28066
Missing (%)50.0%
Infinite0
Infinite (%)0.0%
Mean0.9782616443
Minimum0
Maximum10
Zeros13033
Zeros (%)23.2%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:00.931578image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile4
Maximum10
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.347508188
Coefficient of variation (CV)1.377451724
Kurtosis5.660247772
Mean0.9782616443
Median Absolute Deviation (MAD)1
Skewness2.139512363
Sum27451
Variance1.815778318
MonotonicityNot monotonic
2025-01-04T15:12:01.051742image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 13033
23.2%
1 8937
 
15.9%
2 3149
 
5.6%
3 1332
 
2.4%
4 668
 
1.2%
5 403
 
0.7%
6 323
 
0.6%
7 158
 
0.3%
8 40
 
0.1%
9 11
 
< 0.1%
(Missing) 28066
50.0%
ValueCountFrequency (%)
0 13033
23.2%
1 8937
15.9%
2 3149
 
5.6%
3 1332
 
2.4%
4 668
 
1.2%
ValueCountFrequency (%)
10 7
 
< 0.1%
9 11
 
< 0.1%
8 40
 
0.1%
7 158
0.3%
6 323
0.6%

Counter Attacks - home
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)< 0.1%
Missing28066
Missing (%)50.0%
Infinite0
Infinite (%)0.0%
Mean1.133316703
Minimum0
Maximum13
Zeros11294
Zeros (%)20.1%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:01.170057image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum13
Range13
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.475510014
Coefficient of variation (CV)1.301939705
Kurtosis7.729077543
Mean1.133316703
Median Absolute Deviation (MAD)1
Skewness2.32272039
Sum31802
Variance2.177129801
MonotonicityNot monotonic
2025-01-04T15:12:01.298229image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 11294
20.1%
1 9570
 
17.1%
2 3870
 
6.9%
3 1312
 
2.3%
4 856
 
1.5%
5 513
 
0.9%
6 325
 
0.6%
7 156
 
0.3%
8 73
 
0.1%
11 36
 
0.1%
Other values (4) 56
 
0.1%
(Missing) 28066
50.0%
ValueCountFrequency (%)
0 11294
20.1%
1 9570
17.1%
2 3870
 
6.9%
3 1312
 
2.3%
4 856
 
1.5%
ValueCountFrequency (%)
13 5
 
< 0.1%
12 1
 
< 0.1%
11 36
0.1%
10 18
< 0.1%
9 32
0.1%

Dangerous Attacks - away
Real number (ℝ)

ZEROS 

Distinct127
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.74901563
Minimum0
Maximum163
Zeros2721
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:01.440535image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q17
median16
Q327
95-th percentile46
Maximum163
Range163
Interquartile range (IQR)20

Descriptive statistics

Standard deviation14.93048746
Coefficient of variation (CV)0.7963344723
Kurtosis3.823697598
Mean18.74901563
Median Absolute Deviation (MAD)10
Skewness1.291633396
Sum1052326
Variance222.9194559
MonotonicityNot monotonic
2025-01-04T15:12:01.601873image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2721
 
4.8%
1 1847
 
3.3%
2 1789
 
3.2%
3 1756
 
3.1%
5 1743
 
3.1%
4 1713
 
3.1%
10 1701
 
3.0%
7 1699
 
3.0%
6 1680
 
3.0%
8 1661
 
3.0%
Other values (117) 37817
67.4%
ValueCountFrequency (%)
0 2721
4.8%
1 1847
3.3%
2 1789
3.2%
3 1756
3.1%
4 1713
3.1%
ValueCountFrequency (%)
163 2
< 0.1%
162 1
< 0.1%
160 1
< 0.1%
156 1
< 0.1%
155 2
< 0.1%

Dangerous Attacks - home
Real number (ℝ)

ZEROS 

Distinct130
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.39807936
Minimum0
Maximum140
Zeros2239
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:01.757722image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q19
median19
Q333
95-th percentile54
Maximum140
Range140
Interquartile range (IQR)24

Descriptive statistics

Standard deviation17.24918496
Coefficient of variation (CV)0.7701189324
Kurtosis1.839505356
Mean22.39807936
Median Absolute Deviation (MAD)12
Skewness1.088707206
Sum1257137
Variance297.5343818
MonotonicityNot monotonic
2025-01-04T15:12:02.108900image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2239
 
4.0%
5 1543
 
2.7%
3 1491
 
2.7%
6 1482
 
2.6%
2 1480
 
2.6%
1 1431
 
2.5%
9 1419
 
2.5%
8 1390
 
2.5%
12 1369
 
2.4%
11 1346
 
2.4%
Other values (120) 40937
72.9%
ValueCountFrequency (%)
0 2239
4.0%
1 1431
2.5%
2 1480
2.6%
3 1491
2.7%
4 1339
2.4%
ValueCountFrequency (%)
140 2
< 0.1%
137 1
 
< 0.1%
136 1
 
< 0.1%
134 4
< 0.1%
133 1
 
< 0.1%

Dribble Attempts - away
Real number (ℝ)

ZEROS 

Distinct32
Distinct (%)0.1%
Missing30
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean6.939123304
Minimum0
Maximum31
Zeros3014
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:02.254809image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median6
Q310
95-th percentile17
Maximum31
Range31
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.275292054
Coefficient of variation (CV)0.7602245734
Kurtosis0.3381727905
Mean6.939123304
Median Absolute Deviation (MAD)4
Skewness0.8274176048
Sum389264
Variance27.82870626
MonotonicityNot monotonic
2025-01-04T15:12:02.392444image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 6380
 
11.4%
3 4378
 
7.8%
2 4357
 
7.8%
4 4066
 
7.2%
5 3832
 
6.8%
6 3619
 
6.4%
8 3578
 
6.4%
7 3553
 
6.3%
9 3156
 
5.6%
0 3014
 
5.4%
Other values (22) 16164
28.8%
ValueCountFrequency (%)
0 3014
5.4%
1 6380
11.4%
2 4357
7.8%
3 4378
7.8%
4 4066
7.2%
ValueCountFrequency (%)
31 11
 
< 0.1%
30 3
 
< 0.1%
29 8
 
< 0.1%
28 27
< 0.1%
27 40
0.1%

Dribble Attempts - home
Real number (ℝ)

ZEROS 

Distinct33
Distinct (%)0.1%
Missing30
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean6.956717828
Minimum0
Maximum32
Zeros3100
Zeros (%)5.5%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:02.530427image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median6
Q310
95-th percentile17
Maximum32
Range32
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.35526733
Coefficient of variation (CV)0.7697979797
Kurtosis0.393571035
Mean6.956717828
Median Absolute Deviation (MAD)4
Skewness0.8564556923
Sum390251
Variance28.67888817
MonotonicityNot monotonic
2025-01-04T15:12:02.670117image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1 6379
 
11.4%
2 4578
 
8.2%
3 4164
 
7.4%
4 4108
 
7.3%
5 3854
 
6.9%
6 3626
 
6.5%
7 3598
 
6.4%
8 3277
 
5.8%
9 3144
 
5.6%
0 3100
 
5.5%
Other values (23) 16269
29.0%
ValueCountFrequency (%)
0 3100
5.5%
1 6379
11.4%
2 4578
8.2%
3 4164
7.4%
4 4108
7.3%
ValueCountFrequency (%)
32 4
 
< 0.1%
31 3
 
< 0.1%
30 17
< 0.1%
29 13
< 0.1%
28 20
< 0.1%

Fouls - away
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)< 0.1%
Missing6
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean5.771743198
Minimum0
Maximum24
Zeros2913
Zeros (%)5.2%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:02.804637image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q39
95-th percentile14
Maximum24
Range24
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.24085959
Coefficient of variation (CV)0.7347623491
Kurtosis0.1175951432
Mean5.771743198
Median Absolute Deviation (MAD)3
Skewness0.7562319261
Sum323916
Variance17.98489006
MonotonicityNot monotonic
2025-01-04T15:12:02.940159image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 7016
12.5%
2 5671
10.1%
3 5112
9.1%
4 4685
8.3%
5 4538
8.1%
6 4448
7.9%
7 4019
 
7.2%
8 3403
 
6.1%
9 3279
 
5.8%
0 2913
 
5.2%
Other values (15) 11037
19.7%
ValueCountFrequency (%)
0 2913
5.2%
1 7016
12.5%
2 5671
10.1%
3 5112
9.1%
4 4685
8.3%
ValueCountFrequency (%)
24 4
 
< 0.1%
23 20
 
< 0.1%
22 20
 
< 0.1%
21 51
0.1%
20 120
0.2%

Fouls - home
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)< 0.1%
Missing6
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean5.573118797
Minimum0
Maximum24
Zeros3228
Zeros (%)5.8%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:03.071352image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q38
95-th percentile13
Maximum24
Range24
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.980772138
Coefficient of variation (CV)0.714280869
Kurtosis-0.2421168379
Mean5.573118797
Median Absolute Deviation (MAD)3
Skewness0.6190296775
Sum312769
Variance15.84654681
MonotonicityNot monotonic
2025-01-04T15:12:03.208683image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 6919
12.3%
2 5511
9.8%
4 5097
9.1%
3 5007
8.9%
5 4763
8.5%
6 4241
7.6%
7 4214
7.5%
9 3657
 
6.5%
8 3566
 
6.4%
0 3228
 
5.8%
Other values (15) 9918
17.7%
ValueCountFrequency (%)
0 3228
5.8%
1 6919
12.3%
2 5511
9.8%
3 5007
8.9%
4 5097
9.1%
ValueCountFrequency (%)
24 1
 
< 0.1%
23 5
 
< 0.1%
22 6
 
< 0.1%
21 8
< 0.1%
20 19
< 0.1%

Free Kicks - away
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)0.5%
Missing51070
Missing (%)91.0%
Infinite0
Infinite (%)0.0%
Mean6.490211588
Minimum0
Maximum23
Zeros501
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:03.339463image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median6
Q310
95-th percentile15
Maximum23
Range23
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.766829062
Coefficient of variation (CV)0.7344643542
Kurtosis-0.4359485497
Mean6.490211588
Median Absolute Deviation (MAD)4
Skewness0.5148078362
Sum32821
Variance22.72265931
MonotonicityNot monotonic
2025-01-04T15:12:03.464868image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 501
 
0.9%
4 459
 
0.8%
1 435
 
0.8%
3 357
 
0.6%
6 348
 
0.6%
11 335
 
0.6%
2 330
 
0.6%
8 319
 
0.6%
7 308
 
0.5%
10 297
 
0.5%
Other values (14) 1368
 
2.4%
(Missing) 51070
91.0%
ValueCountFrequency (%)
0 501
0.9%
1 435
0.8%
2 330
0.6%
3 357
0.6%
4 459
0.8%
ValueCountFrequency (%)
23 2
 
< 0.1%
22 3
 
< 0.1%
21 7
 
< 0.1%
20 12
< 0.1%
19 21
< 0.1%

Free Kicks - home
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)0.4%
Missing51070
Missing (%)91.0%
Infinite0
Infinite (%)0.0%
Mean5.783666205
Minimum0
Maximum19
Zeros517
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:03.584413image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q39
95-th percentile13
Maximum19
Range19
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.178790319
Coefficient of variation (CV)0.722515818
Kurtosis-0.6657656493
Mean5.783666205
Median Absolute Deviation (MAD)3
Skewness0.4714497267
Sum29248
Variance17.46228853
MonotonicityNot monotonic
2025-01-04T15:12:03.710401image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 517
 
0.9%
2 459
 
0.8%
3 448
 
0.8%
4 431
 
0.8%
6 424
 
0.8%
5 401
 
0.7%
1 370
 
0.7%
9 359
 
0.6%
7 342
 
0.6%
8 302
 
0.5%
Other values (10) 1004
 
1.8%
(Missing) 51070
91.0%
ValueCountFrequency (%)
0 517
0.9%
1 370
0.7%
2 459
0.8%
3 448
0.8%
4 431
0.8%
ValueCountFrequency (%)
19 1
 
< 0.1%
18 1
 
< 0.1%
17 14
 
< 0.1%
16 25
 
< 0.1%
15 90
0.2%

Goal Attempts - away
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)< 0.1%
Missing8229
Missing (%)14.7%
Infinite0
Infinite (%)0.0%
Mean2.495198129
Minimum0
Maximum17
Zeros9912
Zeros (%)17.7%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:03.836899image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile7
Maximum17
Range17
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.337529823
Coefficient of variation (CV)0.9368113078
Kurtosis1.684854101
Mean2.495198129
Median Absolute Deviation (MAD)1
Skewness1.210109712
Sum119515
Variance5.464045672
MonotonicityNot monotonic
2025-01-04T15:12:03.960292image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
1 10678
19.0%
0 9912
17.7%
2 7981
14.2%
3 5876
10.5%
4 4931
8.8%
5 2693
 
4.8%
6 2398
 
4.3%
7 1699
 
3.0%
8 879
 
1.6%
9 442
 
0.8%
Other values (7) 409
 
0.7%
(Missing) 8229
14.7%
ValueCountFrequency (%)
0 9912
17.7%
1 10678
19.0%
2 7981
14.2%
3 5876
10.5%
4 4931
8.8%
ValueCountFrequency (%)
17 6
 
< 0.1%
15 30
 
0.1%
14 6
 
< 0.1%
13 75
0.1%
12 45
0.1%

Goal Attempts - home
Real number (ℝ)

MISSING  ZEROS 

Distinct21
Distinct (%)< 0.1%
Missing8229
Missing (%)14.7%
Infinite0
Infinite (%)0.0%
Mean3.077539772
Minimum0
Maximum24
Zeros7117
Zeros (%)12.7%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:04.090823image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q35
95-th percentile8
Maximum24
Range24
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.741944254
Coefficient of variation (CV)0.8909533123
Kurtosis2.068163043
Mean3.077539772
Median Absolute Deviation (MAD)2
Skewness1.258299028
Sum147408
Variance7.518258289
MonotonicityNot monotonic
2025-01-04T15:12:04.221346image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 10314
18.4%
2 7314
13.0%
0 7117
12.7%
3 5843
10.4%
4 4687
8.4%
5 4171
7.4%
6 3037
 
5.4%
7 1906
 
3.4%
8 1396
 
2.5%
9 722
 
1.3%
Other values (11) 1391
 
2.5%
(Missing) 8229
14.7%
ValueCountFrequency (%)
0 7117
12.7%
1 10314
18.4%
2 7314
13.0%
3 5843
10.4%
4 4687
8.4%
ValueCountFrequency (%)
24 1
 
< 0.1%
20 19
< 0.1%
19 6
 
< 0.1%
18 2
 
< 0.1%
16 37
0.1%

Goal Kicks - away
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)< 0.1%
Missing560
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean3.600446308
Minimum0
Maximum23
Zeros8009
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:04.348689image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q35
95-th percentile10
Maximum23
Range23
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.15743404
Coefficient of variation (CV)0.8769562909
Kurtosis1.39149035
Mean3.600446308
Median Absolute Deviation (MAD)2
Skewness1.131353779
Sum200066
Variance9.969389716
MonotonicityNot monotonic
2025-01-04T15:12:04.472324image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 9799
17.5%
0 8009
14.3%
2 7597
13.5%
3 6402
11.4%
4 5237
9.3%
5 4987
8.9%
6 3838
 
6.8%
7 3232
 
5.8%
8 2041
 
3.6%
9 1490
 
2.7%
Other values (14) 2935
 
5.2%
ValueCountFrequency (%)
0 8009
14.3%
1 9799
17.5%
2 7597
13.5%
3 6402
11.4%
4 5237
9.3%
ValueCountFrequency (%)
23 2
 
< 0.1%
22 9
< 0.1%
21 2
 
< 0.1%
20 7
< 0.1%
19 2
 
< 0.1%

Goal Kicks - home
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)< 0.1%
Missing560
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean3.018518185
Minimum0
Maximum17
Zeros9116
Zeros (%)16.2%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:04.590881image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q35
95-th percentile8
Maximum17
Range17
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.622226974
Coefficient of variation (CV)0.8687133266
Kurtosis0.9309161935
Mean3.018518185
Median Absolute Deviation (MAD)2
Skewness1.023471289
Sum167730
Variance6.876074304
MonotonicityNot monotonic
2025-01-04T15:12:04.714720image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1 10808
19.3%
0 9116
16.2%
2 8472
15.1%
3 7045
12.6%
4 6039
10.8%
5 4296
 
7.7%
6 3628
 
6.5%
7 2447
 
4.4%
8 1596
 
2.8%
9 857
 
1.5%
Other values (8) 1263
 
2.3%
ValueCountFrequency (%)
0 9116
16.2%
1 10808
19.3%
2 8472
15.1%
3 7045
12.6%
4 6039
10.8%
ValueCountFrequency (%)
17 16
 
< 0.1%
16 11
 
< 0.1%
15 26
 
< 0.1%
14 32
 
0.1%
13 88
0.2%

Goals - away
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5800773246
Minimum0
Maximum5
Zeros32441
Zeros (%)57.8%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:04.834780image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.7862201228
Coefficient of variation (CV)1.35537124
Kurtosis1.25642625
Mean0.5800773246
Median Absolute Deviation (MAD)0
Skewness1.288576109
Sum32558
Variance0.6181420815
MonotonicityNot monotonic
2025-01-04T15:12:04.947527image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 32441
57.8%
1 16296
29.0%
2 6052
 
10.8%
3 1207
 
2.2%
4 118
 
0.2%
5 13
 
< 0.1%
ValueCountFrequency (%)
0 32441
57.8%
1 16296
29.0%
2 6052
 
10.8%
3 1207
 
2.2%
4 118
 
0.2%
ValueCountFrequency (%)
5 13
 
< 0.1%
4 118
 
0.2%
3 1207
 
2.2%
2 6052
 
10.8%
1 16296
29.0%

Goals - home
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6415807009
Minimum0
Maximum5
Zeros30960
Zeros (%)55.2%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:05.057398image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.8422894826
Coefficient of variation (CV)1.312834818
Kurtosis1.225235586
Mean0.6415807009
Median Absolute Deviation (MAD)0
Skewness1.276256841
Sum36010
Variance0.7094515725
MonotonicityNot monotonic
2025-01-04T15:12:05.170777image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 30960
55.2%
1 16637
29.6%
2 6510
 
11.6%
3 1734
 
3.1%
4 279
 
0.5%
5 7
 
< 0.1%
ValueCountFrequency (%)
0 30960
55.2%
1 16637
29.6%
2 6510
 
11.6%
3 1734
 
3.1%
4 279
 
0.5%
ValueCountFrequency (%)
5 7
 
< 0.1%
4 279
 
0.5%
3 1734
 
3.1%
2 6510
 
11.6%
1 16637
29.6%

Headers - away
Real number (ℝ)

MISSING  ZEROS 

Distinct61
Distinct (%)0.1%
Missing4262
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean11.16560301
Minimum0
Maximum61
Zeros2989
Zeros (%)5.3%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:05.308293image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median9
Q317
95-th percentile29
Maximum61
Range61
Interquartile range (IQR)13

Descriptive statistics

Standard deviation9.186998719
Coefficient of variation (CV)0.8227946769
Kurtosis1.155795436
Mean11.16560301
Median Absolute Deviation (MAD)6
Skewness1.056101933
Sum579104
Variance84.40094547
MonotonicityNot monotonic
2025-01-04T15:12:05.463916image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 3741
 
6.7%
2 3145
 
5.6%
0 2989
 
5.3%
4 2926
 
5.2%
6 2451
 
4.4%
3 2354
 
4.2%
5 2349
 
4.2%
8 2264
 
4.0%
9 2204
 
3.9%
7 2117
 
3.8%
Other values (51) 25325
45.1%
(Missing) 4262
 
7.6%
ValueCountFrequency (%)
0 2989
5.3%
1 3741
6.7%
2 3145
5.6%
3 2354
4.2%
4 2926
5.2%
ValueCountFrequency (%)
61 2
 
< 0.1%
60 1
 
< 0.1%
59 5
< 0.1%
58 8
< 0.1%
57 4
< 0.1%

Headers - home
Real number (ℝ)

MISSING  ZEROS 

Distinct65
Distinct (%)0.1%
Missing4262
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean11.92141136
Minimum0
Maximum69
Zeros2864
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:05.620421image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median10
Q318
95-th percentile31
Maximum69
Range69
Interquartile range (IQR)14

Descriptive statistics

Standard deviation9.89654342
Coefficient of variation (CV)0.8301486396
Kurtosis0.9403325804
Mean11.92141136
Median Absolute Deviation (MAD)7
Skewness1.026502317
Sum618304
Variance97.94157166
MonotonicityNot monotonic
2025-01-04T15:12:05.783360image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 3789
 
6.8%
2 3214
 
5.7%
0 2864
 
5.1%
4 2576
 
4.6%
7 2347
 
4.2%
6 2245
 
4.0%
3 2211
 
3.9%
5 2209
 
3.9%
8 2154
 
3.8%
10 2036
 
3.6%
Other values (55) 26220
46.7%
(Missing) 4262
 
7.6%
ValueCountFrequency (%)
0 2864
5.1%
1 3789
6.8%
2 3214
5.7%
3 2211
3.9%
4 2576
4.6%
ValueCountFrequency (%)
69 3
< 0.1%
65 2
 
< 0.1%
64 6
< 0.1%
62 3
< 0.1%
61 1
 
< 0.1%

Hit Woodwork - away
Real number (ℝ)

ZEROS 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1357279028
Minimum0
Maximum3
Zeros49363
Zeros (%)87.9%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:05.910674image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum3
Range3
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3859417288
Coefficient of variation (CV)2.843495853
Kurtosis9.140146683
Mean0.1357279028
Median Absolute Deviation (MAD)0
Skewness2.977216607
Sum7618
Variance0.148951018
MonotonicityNot monotonic
2025-01-04T15:12:06.019142image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
0 49363
87.9%
1 5944
 
10.6%
2 786
 
1.4%
3 34
 
0.1%
ValueCountFrequency (%)
0 49363
87.9%
1 5944
 
10.6%
2 786
 
1.4%
3 34
 
0.1%
ValueCountFrequency (%)
3 34
 
0.1%
2 786
 
1.4%
1 5944
 
10.6%
0 49363
87.9%

Hit Woodwork - home
Real number (ℝ)

ZEROS 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1505336113
Minimum0
Maximum3
Zeros48713
Zeros (%)86.8%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:06.126700image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum3
Range3
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.409920922
Coefficient of variation (CV)2.7231189
Kurtosis9.253007356
Mean0.1505336113
Median Absolute Deviation (MAD)0
Skewness2.926220707
Sum8449
Variance0.1680351623
MonotonicityNot monotonic
2025-01-04T15:12:06.235255image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
0 48713
86.8%
1 6471
 
11.5%
2 851
 
1.5%
3 92
 
0.2%
ValueCountFrequency (%)
0 48713
86.8%
1 6471
 
11.5%
2 851
 
1.5%
3 92
 
0.2%
ValueCountFrequency (%)
3 92
 
0.2%
2 851
 
1.5%
1 6471
 
11.5%
0 48713
86.8%

Injuries - away
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)< 0.1%
Missing25464
Missing (%)45.4%
Infinite0
Infinite (%)0.0%
Mean0.6560675733
Minimum0
Maximum5
Zeros15353
Zeros (%)27.4%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:06.346464image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.7809637618
Coefficient of variation (CV)1.190370922
Kurtosis1.321080798
Mean0.6560675733
Median Absolute Deviation (MAD)0
Skewness1.17469767
Sum20117
Variance0.6099043972
MonotonicityNot monotonic
2025-01-04T15:12:06.460939image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 15353
27.4%
1 11483
20.5%
2 2946
 
5.2%
3 787
 
1.4%
4 89
 
0.2%
5 5
 
< 0.1%
(Missing) 25464
45.4%
ValueCountFrequency (%)
0 15353
27.4%
1 11483
20.5%
2 2946
 
5.2%
3 787
 
1.4%
4 89
 
0.2%
ValueCountFrequency (%)
5 5
 
< 0.1%
4 89
 
0.2%
3 787
 
1.4%
2 2946
 
5.2%
1 11483
20.5%

Injuries - home
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)< 0.1%
Missing25464
Missing (%)45.4%
Infinite0
Infinite (%)0.0%
Mean0.5334442162
Minimum0
Maximum5
Zeros17556
Zeros (%)31.3%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:06.572157image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.7311533701
Coefficient of variation (CV)1.370627608
Kurtosis4.614354807
Mean0.5334442162
Median Absolute Deviation (MAD)0
Skewness1.723533826
Sum16357
Variance0.5345852507
MonotonicityNot monotonic
2025-01-04T15:12:06.687211image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 17556
31.3%
1 10702
19.1%
2 1776
 
3.2%
3 482
 
0.9%
4 78
 
0.1%
5 69
 
0.1%
(Missing) 25464
45.4%
ValueCountFrequency (%)
0 17556
31.3%
1 10702
19.1%
2 1776
 
3.2%
3 482
 
0.9%
4 78
 
0.1%
ValueCountFrequency (%)
5 69
 
0.1%
4 78
 
0.1%
3 482
 
0.9%
2 1776
 
3.2%
1 10702
19.1%

Interceptions - away
Real number (ℝ)

ZEROS 

Distinct22
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.08348923
Minimum0
Maximum21
Zeros6592
Zeros (%)11.7%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:06.810859image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q36
95-th percentile10
Maximum21
Range21
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.214500655
Coefficient of variation (CV)0.787194596
Kurtosis0.5110861651
Mean4.08348923
Median Absolute Deviation (MAD)2
Skewness0.8573890513
Sum229194
Variance10.33301446
MonotonicityNot monotonic
2025-01-04T15:12:06.935534image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 7529
13.4%
2 7195
12.8%
0 6592
11.7%
3 6549
11.7%
4 5895
10.5%
5 5669
10.1%
6 4656
8.3%
7 3725
6.6%
8 2670
 
4.8%
9 1776
 
3.2%
Other values (12) 3871
6.9%
ValueCountFrequency (%)
0 6592
11.7%
1 7529
13.4%
2 7195
12.8%
3 6549
11.7%
4 5895
10.5%
ValueCountFrequency (%)
21 4
 
< 0.1%
20 4
 
< 0.1%
19 12
 
< 0.1%
18 8
 
< 0.1%
17 41
0.1%

Interceptions - home
Real number (ℝ)

ZEROS 

Distinct23
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.047624138
Minimum0
Maximum22
Zeros6304
Zeros (%)11.2%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:07.062286image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q36
95-th percentile10
Maximum22
Range22
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.293984124
Coefficient of variation (CV)0.8138068189
Kurtosis1.081625274
Mean4.047624138
Median Absolute Deviation (MAD)2
Skewness1.021403635
Sum227181
Variance10.85033141
MonotonicityNot monotonic
2025-01-04T15:12:07.182832image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 8446
15.0%
2 7167
12.8%
3 6874
12.2%
0 6304
11.2%
4 5893
10.5%
5 5671
10.1%
6 3979
7.1%
7 3265
 
5.8%
8 2516
 
4.5%
9 1909
 
3.4%
Other values (13) 4103
7.3%
ValueCountFrequency (%)
0 6304
11.2%
1 8446
15.0%
2 7167
12.8%
3 6874
12.2%
4 5893
10.5%
ValueCountFrequency (%)
22 3
 
< 0.1%
21 22
< 0.1%
20 25
< 0.1%
19 8
 
< 0.1%
18 27
< 0.1%

Key Passes - away
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)< 0.1%
Missing6
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3.755831151
Minimum0
Maximum20
Zeros9347
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:07.488448image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q36
95-th percentile10
Maximum20
Range20
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.30018994
Coefficient of variation (CV)0.8786843198
Kurtosis0.7796999812
Mean3.755831151
Median Absolute Deviation (MAD)2
Skewness0.98741917
Sum210781
Variance10.89125364
MonotonicityNot monotonic
2025-01-04T15:12:07.621127image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 9347
16.7%
1 8680
15.5%
2 6539
11.7%
3 5896
10.5%
4 5594
10.0%
5 4896
8.7%
6 3969
7.1%
7 3564
 
6.3%
8 2540
 
4.5%
9 1579
 
2.8%
Other values (11) 3517
 
6.3%
ValueCountFrequency (%)
0 9347
16.7%
1 8680
15.5%
2 6539
11.7%
3 5896
10.5%
4 5594
10.0%
ValueCountFrequency (%)
20 4
 
< 0.1%
19 11
 
< 0.1%
18 32
 
0.1%
17 86
0.2%
16 47
0.1%

Key Passes - home
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)< 0.1%
Missing6
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean4.601076246
Minimum0
Maximum25
Zeros7224
Zeros (%)12.9%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:07.758253image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q37
95-th percentile12
Maximum25
Range25
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.835426117
Coefficient of variation (CV)0.8335932533
Kurtosis0.717284113
Mean4.601076246
Median Absolute Deviation (MAD)3
Skewness0.9516929356
Sum258217
Variance14.7104935
MonotonicityNot monotonic
2025-01-04T15:12:07.894336image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 7362
13.1%
0 7224
12.9%
2 5819
10.4%
3 5416
9.6%
4 5387
9.6%
5 4743
8.5%
6 4639
8.3%
7 3964
7.1%
8 2873
 
5.1%
9 2485
 
4.4%
Other values (16) 6209
11.1%
ValueCountFrequency (%)
0 7224
12.9%
1 7362
13.1%
2 5819
10.4%
3 5416
9.6%
4 5387
9.6%
ValueCountFrequency (%)
25 4
 
< 0.1%
24 5
< 0.1%
23 11
< 0.1%
22 11
< 0.1%
21 11
< 0.1%

Long Passes - away
Real number (ℝ)

MISSING  ZEROS 

Distinct51
Distinct (%)0.1%
Missing2010
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean10.5100061
Minimum0
Maximum51
Zeros3086
Zeros (%)5.5%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:08.042611image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median10
Q315
95-th percentile24
Maximum51
Range51
Interquartile range (IQR)11

Descriptive statistics

Standard deviation7.500486386
Coefficient of variation (CV)0.7136519538
Kurtosis0.3143274548
Mean10.5100061
Median Absolute Deviation (MAD)6
Skewness0.6888198613
Sum568770
Variance56.25729603
MonotonicityNot monotonic
2025-01-04T15:12:08.201669image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3086
 
5.5%
1 3054
 
5.4%
8 2907
 
5.2%
2 2631
 
4.7%
6 2626
 
4.7%
3 2600
 
4.6%
5 2573
 
4.6%
7 2507
 
4.5%
10 2496
 
4.4%
11 2483
 
4.4%
Other values (41) 27154
48.4%
ValueCountFrequency (%)
0 3086
5.5%
1 3054
5.4%
2 2631
4.7%
3 2600
4.6%
4 2402
4.3%
ValueCountFrequency (%)
51 2
 
< 0.1%
50 3
 
< 0.1%
48 2
 
< 0.1%
47 3
 
< 0.1%
46 17
< 0.1%

Long Passes - home
Real number (ℝ)

MISSING  ZEROS 

Distinct45
Distinct (%)0.1%
Missing2010
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean10.89106935
Minimum0
Maximum45
Zeros3013
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:08.354086image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median10
Q316
95-th percentile25
Maximum45
Range45
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.817007341
Coefficient of variation (CV)0.7177447035
Kurtosis0.0291053501
Mean10.89106935
Median Absolute Deviation (MAD)6
Skewness0.670001239
Sum589392
Variance61.10560377
MonotonicityNot monotonic
2025-01-04T15:12:08.500670image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 3013
 
5.4%
1 2841
 
5.1%
7 2657
 
4.7%
4 2637
 
4.7%
3 2630
 
4.7%
8 2607
 
4.6%
5 2567
 
4.6%
6 2521
 
4.5%
2 2442
 
4.4%
9 2435
 
4.3%
Other values (35) 27767
49.5%
ValueCountFrequency (%)
0 3013
5.4%
1 2841
5.1%
2 2442
4.4%
3 2630
4.7%
4 2637
4.7%
ValueCountFrequency (%)
45 5
 
< 0.1%
44 4
 
< 0.1%
42 8
 
< 0.1%
41 23
< 0.1%
40 21
< 0.1%

Offsides - away
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)< 0.1%
Missing2823
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean0.8697658712
Minimum0
Maximum7
Zeros23853
Zeros (%)42.5%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:08.620102image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.036525184
Coefficient of variation (CV)1.191728967
Kurtosis2.491199761
Mean0.8697658712
Median Absolute Deviation (MAD)1
Skewness1.466581102
Sum46362
Variance1.074384456
MonotonicityNot monotonic
2025-01-04T15:12:08.733581image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 23853
42.5%
1 18720
33.4%
2 6514
 
11.6%
3 2705
 
4.8%
4 1153
 
2.1%
5 285
 
0.5%
6 56
 
0.1%
7 18
 
< 0.1%
(Missing) 2823
 
5.0%
ValueCountFrequency (%)
0 23853
42.5%
1 18720
33.4%
2 6514
 
11.6%
3 2705
 
4.8%
4 1153
 
2.1%
ValueCountFrequency (%)
7 18
 
< 0.1%
6 56
 
0.1%
5 285
 
0.5%
4 1153
2.1%
3 2705
4.8%

Offsides - home
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)< 0.1%
Missing2823
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean1.070538796
Minimum0
Maximum10
Zeros20980
Zeros (%)37.4%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:08.855783image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum10
Range10
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.249676048
Coefficient of variation (CV)1.167333732
Kurtosis4.847303623
Mean1.070538796
Median Absolute Deviation (MAD)1
Skewness1.784821373
Sum57064
Variance1.561690226
MonotonicityNot monotonic
2025-01-04T15:12:08.970846image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 20980
37.4%
1 18368
32.7%
2 7701
 
13.7%
3 3644
 
6.5%
4 1656
 
3.0%
5 452
 
0.8%
6 227
 
0.4%
7 136
 
0.2%
8 108
 
0.2%
9 20
 
< 0.1%
(Missing) 2823
 
5.0%
ValueCountFrequency (%)
0 20980
37.4%
1 18368
32.7%
2 7701
 
13.7%
3 3644
 
6.5%
4 1656
 
3.0%
ValueCountFrequency (%)
10 12
 
< 0.1%
9 20
 
< 0.1%
8 108
0.2%
7 136
0.2%
6 227
0.4%

Passes - away
Real number (ℝ)

Distinct710
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean208.2638659
Minimum0
Maximum841
Zeros521
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:09.110647image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile17
Q197
median194
Q3300
95-th percentile457
Maximum841
Range841
Interquartile range (IQR)203

Descriptive statistics

Standard deviation137.8342163
Coefficient of variation (CV)0.6618249196
Kurtosis-0.01338517318
Mean208.2638659
Median Absolute Deviation (MAD)101
Skewness0.5999667082
Sum11689226
Variance18998.27118
MonotonicityNot monotonic
2025-01-04T15:12:09.261394image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 521
 
0.9%
1 269
 
0.5%
2 200
 
0.4%
127 192
 
0.3%
126 189
 
0.3%
97 186
 
0.3%
151 184
 
0.3%
125 182
 
0.3%
191 178
 
0.3%
170 178
 
0.3%
Other values (700) 53848
95.9%
ValueCountFrequency (%)
0 521
0.9%
1 269
0.5%
2 200
 
0.4%
3 132
 
0.2%
4 155
 
0.3%
ValueCountFrequency (%)
841 1
 
< 0.1%
835 1
 
< 0.1%
830 4
< 0.1%
827 2
< 0.1%
810 3
< 0.1%

Passes - home
Real number (ℝ)

ZEROS 

Distinct698
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean214.3021719
Minimum0
Maximum776
Zeros590
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:09.417765image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile17
Q1101
median201
Q3309
95-th percentile465
Maximum776
Range776
Interquartile range (IQR)208

Descriptive statistics

Standard deviation139.5772216
Coefficient of variation (CV)0.6513103455
Kurtosis-0.2680503836
Mean214.3021719
Median Absolute Deviation (MAD)104
Skewness0.5193359557
Sum12028138
Variance19481.80079
MonotonicityNot monotonic
2025-01-04T15:12:09.583624image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 590
 
1.1%
112 206
 
0.4%
1 204
 
0.4%
167 190
 
0.3%
2 188
 
0.3%
171 185
 
0.3%
53 181
 
0.3%
218 181
 
0.3%
176 181
 
0.3%
92 180
 
0.3%
Other values (688) 53841
95.9%
ValueCountFrequency (%)
0 590
1.1%
1 204
 
0.4%
2 188
 
0.3%
3 153
 
0.3%
4 106
 
0.2%
ValueCountFrequency (%)
776 2
< 0.1%
761 3
< 0.1%
758 1
 
< 0.1%
752 4
< 0.1%
749 2
< 0.1%

Penalties - away
Real number (ℝ)

ZEROS 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.06782831792
Minimum0
Maximum3
Zeros52712
Zeros (%)93.9%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:09.712890image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum3
Range3
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2803973945
Coefficient of variation (CV)4.133928174
Kurtosis24.72806327
Mean0.06782831792
Median Absolute Deviation (MAD)0
Skewness4.625887293
Sum3807
Variance0.07862269881
MonotonicityNot monotonic
2025-01-04T15:12:09.827342image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
0 52712
93.9%
1 3063
 
5.5%
2 312
 
0.6%
3 40
 
0.1%
ValueCountFrequency (%)
0 52712
93.9%
1 3063
 
5.5%
2 312
 
0.6%
3 40
 
0.1%
ValueCountFrequency (%)
3 40
 
0.1%
2 312
 
0.6%
1 3063
 
5.5%
0 52712
93.9%

Penalties - home
Real number (ℝ)

ZEROS 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08201044061
Minimum0
Maximum2
Zeros51789
Zeros (%)92.3%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:09.937800image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum2
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2910826489
Coefficient of variation (CV)3.549336483
Kurtosis13.08614627
Mean0.08201044061
Median Absolute Deviation (MAD)0
Skewness3.606453383
Sum4603
Variance0.08472910847
MonotonicityNot monotonic
2025-01-04T15:12:10.055258image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
0 51789
92.3%
1 4073
 
7.3%
2 265
 
0.5%
ValueCountFrequency (%)
0 51789
92.3%
1 4073
 
7.3%
2 265
 
0.5%
ValueCountFrequency (%)
2 265
 
0.5%
1 4073
 
7.3%
0 51789
92.3%

Redcards - away
Real number (ℝ)

ZEROS 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03060915424
Minimum0
Maximum2
Zeros54472
Zeros (%)97.1%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:10.171997image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum2
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1786552867
Coefficient of variation (CV)5.836661976
Kurtosis38.16690085
Mean0.03060915424
Median Absolute Deviation (MAD)0
Skewness6.030262144
Sum1718
Variance0.03191771145
MonotonicityNot monotonic
2025-01-04T15:12:10.289967image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
0 54472
97.1%
1 1592
 
2.8%
2 63
 
0.1%
ValueCountFrequency (%)
0 54472
97.1%
1 1592
 
2.8%
2 63
 
0.1%
ValueCountFrequency (%)
2 63
 
0.1%
1 1592
 
2.8%
0 54472
97.1%

Redcards - home
Real number (ℝ)

ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03007465213
Minimum0
Maximum1
Zeros54439
Zeros (%)97.0%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:10.412757image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1707942831
Coefficient of variation (CV)5.679011096
Kurtosis28.2842261
Mean0.03007465213
Median Absolute Deviation (MAD)0
Skewness5.503019011
Sum1688
Variance0.02917068715
MonotonicityNot monotonic
2025-01-04T15:12:10.523498image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 54439
97.0%
1 1688
 
3.0%
ValueCountFrequency (%)
0 54439
97.0%
1 1688
 
3.0%
ValueCountFrequency (%)
1 1688
 
3.0%
0 54439
97.0%

Saves - away
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)< 0.1%
Missing198
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean1.589926514
Minimum0
Maximum12
Zeros14816
Zeros (%)26.4%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:10.637919image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile5
Maximum12
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.566402983
Coefficient of variation (CV)0.9852046427
Kurtosis2.32729711
Mean1.589926514
Median Absolute Deviation (MAD)1
Skewness1.360617932
Sum88923
Variance2.453618306
MonotonicityNot monotonic
2025-01-04T15:12:10.764668image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 18363
32.7%
0 14816
26.4%
2 9933
17.7%
3 6120
 
10.9%
4 3626
 
6.5%
5 1648
 
2.9%
6 780
 
1.4%
7 406
 
0.7%
8 116
 
0.2%
9 86
 
0.2%
Other values (2) 35
 
0.1%
(Missing) 198
 
0.4%
ValueCountFrequency (%)
0 14816
26.4%
1 18363
32.7%
2 9933
17.7%
3 6120
 
10.9%
4 3626
 
6.5%
ValueCountFrequency (%)
12 8
 
< 0.1%
10 27
 
< 0.1%
9 86
 
0.2%
8 116
 
0.2%
7 406
0.7%

Saves - home
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)< 0.1%
Missing198
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean1.240912586
Minimum0
Maximum8
Zeros20188
Zeros (%)36.0%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:10.885675image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum8
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.35559854
Coefficient of variation (CV)1.092420655
Kurtosis2.02274819
Mean1.240912586
Median Absolute Deviation (MAD)1
Skewness1.368251159
Sum69403
Variance1.837647401
MonotonicityNot monotonic
2025-01-04T15:12:11.006071image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 20188
36.0%
1 17624
31.4%
2 9253
16.5%
3 4801
 
8.6%
4 2411
 
4.3%
5 932
 
1.7%
6 504
 
0.9%
7 186
 
0.3%
8 30
 
0.1%
(Missing) 198
 
0.4%
ValueCountFrequency (%)
0 20188
36.0%
1 17624
31.4%
2 9253
16.5%
3 4801
 
8.6%
4 2411
 
4.3%
ValueCountFrequency (%)
8 30
 
0.1%
7 186
 
0.3%
6 504
 
0.9%
5 932
 
1.7%
4 2411
4.3%

Score Change - away
Real number (ℝ)

ZEROS 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.009229069788
Minimum-1
Maximum2
Zeros55491
Zeros (%)98.9%
Negative60
Negative (%)0.1%
Memory size438.6 KiB
2025-01-04T15:12:11.147475image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum2
Range3
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1065522019
Coefficient of variation (CV)11.54528077
Kurtosis86.40788689
Mean0.009229069788
Median Absolute Deviation (MAD)0
Skewness7.545699726
Sum518
Variance0.01135337173
MonotonicityNot monotonic
2025-01-04T15:12:11.255543image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
0 55491
98.9%
1 574
 
1.0%
-1 60
 
0.1%
2 2
 
< 0.1%
ValueCountFrequency (%)
-1 60
 
0.1%
0 55491
98.9%
1 574
 
1.0%
2 2
 
< 0.1%
ValueCountFrequency (%)
2 2
 
< 0.1%
1 574
 
1.0%
0 55491
98.9%
-1 60
 
0.1%

Score Change - home
Real number (ℝ)

ZEROS 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01003082296
Minimum-1
Maximum2
Zeros55401
Zeros (%)98.7%
Negative82
Negative (%)0.1%
Memory size438.6 KiB
2025-01-04T15:12:11.364492image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum2
Range3
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1135253871
Coefficient of variation (CV)11.31765436
Kurtosis74.09064165
Mean0.01003082296
Median Absolute Deviation (MAD)0
Skewness6.663453306
Sum563
Variance0.01288801352
MonotonicityNot monotonic
2025-01-04T15:12:11.473808image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
0 55401
98.7%
1 643
 
1.1%
-1 82
 
0.1%
2 1
 
< 0.1%
ValueCountFrequency (%)
-1 82
 
0.1%
0 55401
98.7%
1 643
 
1.1%
2 1
 
< 0.1%
ValueCountFrequency (%)
2 1
 
< 0.1%
1 643
 
1.1%
0 55401
98.7%
-1 82
 
0.1%

Shots Blocked - away
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.421526182
Minimum0
Maximum12
Zeros20782
Zeros (%)37.0%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:11.592432image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile5
Maximum12
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.622939554
Coefficient of variation (CV)1.14168812
Kurtosis3.261836176
Mean1.421526182
Median Absolute Deviation (MAD)1
Skewness1.552905619
Sum79786
Variance2.633932795
MonotonicityNot monotonic
2025-01-04T15:12:11.717012image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 20782
37.0%
1 14376
25.6%
2 9285
16.5%
3 5736
 
10.2%
4 2813
 
5.0%
5 1696
 
3.0%
6 786
 
1.4%
7 389
 
0.7%
10 96
 
0.2%
8 93
 
0.2%
Other values (3) 75
 
0.1%
ValueCountFrequency (%)
0 20782
37.0%
1 14376
25.6%
2 9285
16.5%
3 5736
 
10.2%
4 2813
 
5.0%
ValueCountFrequency (%)
12 26
 
< 0.1%
11 2
 
< 0.1%
10 96
0.2%
9 47
0.1%
8 93
0.2%

Shots Blocked - home
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.678782048
Minimum0
Maximum12
Zeros18750
Zeros (%)33.4%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:11.834553image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile5
Maximum12
Range12
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.851985423
Coefficient of variation (CV)1.103172044
Kurtosis2.262145465
Mean1.678782048
Median Absolute Deviation (MAD)1
Skewness1.420875659
Sum94225
Variance3.429850008
MonotonicityNot monotonic
2025-01-04T15:12:11.970715image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 18750
33.4%
1 13855
24.7%
2 8861
15.8%
3 5804
 
10.3%
4 4099
 
7.3%
5 2164
 
3.9%
6 1322
 
2.4%
7 661
 
1.2%
8 275
 
0.5%
9 176
 
0.3%
Other values (3) 160
 
0.3%
ValueCountFrequency (%)
0 18750
33.4%
1 13855
24.7%
2 8861
15.8%
3 5804
 
10.3%
4 4099
 
7.3%
ValueCountFrequency (%)
12 7
 
< 0.1%
11 63
 
0.1%
10 90
 
0.2%
9 176
0.3%
8 275
0.5%

Shots Insidebox - away
Real number (ℝ)

ZEROS 

Distinct20
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.133465177
Minimum0
Maximum19
Zeros11801
Zeros (%)21.0%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:12.094786image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q35
95-th percentile9
Maximum19
Range19
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.943919923
Coefficient of variation (CV)0.939509379
Kurtosis1.266031924
Mean3.133465177
Median Absolute Deviation (MAD)2
Skewness1.121731723
Sum175872
Variance8.666664511
MonotonicityNot monotonic
2025-01-04T15:12:12.225239image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 11801
21.0%
1 9200
16.4%
2 7577
13.5%
3 6425
11.4%
4 5545
9.9%
5 4268
 
7.6%
6 3777
 
6.7%
7 2402
 
4.3%
8 1758
 
3.1%
9 1309
 
2.3%
Other values (10) 2065
 
3.7%
ValueCountFrequency (%)
0 11801
21.0%
1 9200
16.4%
2 7577
13.5%
3 6425
11.4%
4 5545
9.9%
ValueCountFrequency (%)
19 5
 
< 0.1%
18 22
 
< 0.1%
17 59
0.1%
16 28
< 0.1%
15 42
0.1%

Shots Insidebox - home
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.967983324
Minimum0
Maximum27
Zeros9526
Zeros (%)17.0%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:12.361269image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q36
95-th percentile11
Maximum27
Range27
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.515861874
Coefficient of variation (CV)0.8860576236
Kurtosis1.250112921
Mean3.967983324
Median Absolute Deviation (MAD)2
Skewness1.089130051
Sum222711
Variance12.36128472
MonotonicityNot monotonic
2025-01-04T15:12:12.496200image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 9526
17.0%
1 6924
12.3%
2 6847
12.2%
3 6551
11.7%
4 5661
10.1%
5 4445
7.9%
6 4122
7.3%
7 3255
 
5.8%
8 2499
 
4.5%
9 2017
 
3.6%
Other values (15) 4280
7.6%
ValueCountFrequency (%)
0 9526
17.0%
1 6924
12.3%
2 6847
12.2%
3 6551
11.7%
4 5661
10.1%
ValueCountFrequency (%)
27 1
 
< 0.1%
26 4
 
< 0.1%
24 10
< 0.1%
21 13
< 0.1%
20 21
< 0.1%

Shots Off Target - away
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.967199387
Minimum0
Maximum12
Zeros15584
Zeros (%)27.8%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:12.618292image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile6
Maximum12
Range12
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.967417189
Coefficient of variation (CV)1.000110716
Kurtosis1.402305164
Mean1.967199387
Median Absolute Deviation (MAD)1
Skewness1.21324868
Sum110413
Variance3.870730394
MonotonicityNot monotonic
2025-01-04T15:12:12.942084image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 15584
27.8%
1 12575
22.4%
2 10137
18.1%
3 7027
12.5%
4 4583
 
8.2%
5 2613
 
4.7%
6 1743
 
3.1%
7 906
 
1.6%
8 550
 
1.0%
9 237
 
0.4%
Other values (3) 172
 
0.3%
ValueCountFrequency (%)
0 15584
27.8%
1 12575
22.4%
2 10137
18.1%
3 7027
12.5%
4 4583
 
8.2%
ValueCountFrequency (%)
12 1
 
< 0.1%
11 31
 
0.1%
10 140
 
0.2%
9 237
0.4%
8 550
1.0%

Shots Off Target - home
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.408127995
Minimum0
Maximum17
Zeros13281
Zeros (%)23.7%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:13.069082image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile7
Maximum17
Range17
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.252912735
Coefficient of variation (CV)0.9355452616
Kurtosis1.675765784
Mean2.408127995
Median Absolute Deviation (MAD)2
Skewness1.137002897
Sum135161
Variance5.075615793
MonotonicityNot monotonic
2025-01-04T15:12:13.201107image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 13281
23.7%
1 10489
18.7%
2 9672
17.2%
3 7267
12.9%
4 5917
10.5%
5 3754
 
6.7%
6 2492
 
4.4%
7 1643
 
2.9%
8 766
 
1.4%
9 415
 
0.7%
Other values (8) 431
 
0.8%
ValueCountFrequency (%)
0 13281
23.7%
1 10489
18.7%
2 9672
17.2%
3 7267
12.9%
4 5917
10.5%
ValueCountFrequency (%)
17 26
< 0.1%
16 7
 
< 0.1%
15 5
 
< 0.1%
14 2
 
< 0.1%
13 13
< 0.1%

Shots On Target - away
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.766458211
Minimum0
Maximum11
Zeros17076
Zeros (%)30.4%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:13.329271image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile5
Maximum11
Range11
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.769665717
Coefficient of variation (CV)1.001815784
Kurtosis1.224138215
Mean1.766458211
Median Absolute Deviation (MAD)1
Skewness1.134347431
Sum99146
Variance3.131716749
MonotonicityNot monotonic
2025-01-04T15:12:13.450978image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 17076
30.4%
1 12426
22.1%
2 10555
18.8%
3 7190
12.8%
4 4233
 
7.5%
5 2404
 
4.3%
6 1223
 
2.2%
7 612
 
1.1%
8 273
 
0.5%
9 82
 
0.1%
Other values (2) 53
 
0.1%
ValueCountFrequency (%)
0 17076
30.4%
1 12426
22.1%
2 10555
18.8%
3 7190
12.8%
4 4233
 
7.5%
ValueCountFrequency (%)
11 14
 
< 0.1%
10 39
 
0.1%
9 82
 
0.1%
8 273
0.5%
7 612
1.1%

Shots On Target - home
Real number (ℝ)

ZEROS 

Distinct16
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.14082349
Minimum0
Maximum15
Zeros13824
Zeros (%)24.6%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:13.569504image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile6
Maximum15
Range15
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.020724904
Coefficient of variation (CV)0.943900753
Kurtosis1.350170407
Mean2.14082349
Median Absolute Deviation (MAD)1
Skewness1.115967464
Sum120158
Variance4.083329137
MonotonicityNot monotonic
2025-01-04T15:12:13.702424image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 13824
24.6%
1 12228
21.8%
2 10052
17.9%
3 7446
13.3%
4 5034
 
9.0%
5 3548
 
6.3%
6 2109
 
3.8%
7 940
 
1.7%
8 499
 
0.9%
9 278
 
0.5%
Other values (6) 169
 
0.3%
ValueCountFrequency (%)
0 13824
24.6%
1 12228
21.8%
2 10052
17.9%
3 7446
13.3%
4 5034
 
9.0%
ValueCountFrequency (%)
15 2
 
< 0.1%
14 6
 
< 0.1%
13 26
< 0.1%
12 22
< 0.1%
11 38
0.1%

Shots Outsidebox - away
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.795232241
Minimum0
Maximum14
Zeros17391
Zeros (%)31.0%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:13.825308image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile5
Maximum14
Range14
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.884845443
Coefficient of variation (CV)1.049917331
Kurtosis2.090274269
Mean1.795232241
Median Absolute Deviation (MAD)1
Skewness1.333220515
Sum100761
Variance3.552642343
MonotonicityNot monotonic
2025-01-04T15:12:13.949924image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 17391
31.0%
1 13006
23.2%
2 9613
17.1%
3 6658
 
11.9%
4 4278
 
7.6%
5 2422
 
4.3%
6 1244
 
2.2%
7 755
 
1.3%
8 475
 
0.8%
9 196
 
0.3%
Other values (5) 89
 
0.2%
ValueCountFrequency (%)
0 17391
31.0%
1 13006
23.2%
2 9613
17.1%
3 6658
 
11.9%
4 4278
 
7.6%
ValueCountFrequency (%)
14 11
 
< 0.1%
13 13
 
< 0.1%
12 6
 
< 0.1%
11 35
0.1%
10 24
< 0.1%

Shots Outsidebox - home
Real number (ℝ)

ZEROS 

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.999768382
Minimum0
Maximum18
Zeros15508
Zeros (%)27.6%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:14.076656image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile6
Maximum18
Range18
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.018166598
Coefficient of variation (CV)1.009200173
Kurtosis2.452925118
Mean1.999768382
Median Absolute Deviation (MAD)1
Skewness1.336788284
Sum112241
Variance4.072996419
MonotonicityNot monotonic
2025-01-04T15:12:14.204347image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 15508
27.6%
1 12679
22.6%
2 9594
17.1%
3 7052
12.6%
4 4705
 
8.4%
5 3051
 
5.4%
6 1711
 
3.0%
7 836
 
1.5%
8 426
 
0.8%
9 284
 
0.5%
Other values (7) 281
 
0.5%
ValueCountFrequency (%)
0 15508
27.6%
1 12679
22.6%
2 9594
17.1%
3 7052
12.6%
4 4705
 
8.4%
ValueCountFrequency (%)
18 1
 
< 0.1%
17 10
 
< 0.1%
16 7
 
< 0.1%
15 2
 
< 0.1%
12 27
< 0.1%

Shots Total - away
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.065369608
Minimum0
Maximum24
Zeros7911
Zeros (%)14.1%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:14.338899image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median4
Q38
95-th percentile13
Maximum24
Range24
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.261515772
Coefficient of variation (CV)0.8413040117
Kurtosis0.5359894764
Mean5.065369608
Median Absolute Deviation (MAD)3
Skewness0.8966506952
Sum284304
Variance18.16051668
MonotonicityNot monotonic
2025-01-04T15:12:14.473287image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 7911
14.1%
1 6064
10.8%
2 5478
9.8%
4 4842
8.6%
3 4793
8.5%
5 4724
8.4%
7 3770
6.7%
6 3752
6.7%
8 2958
 
5.3%
9 2956
 
5.3%
Other values (15) 8879
15.8%
ValueCountFrequency (%)
0 7911
14.1%
1 6064
10.8%
2 5478
9.8%
3 4793
8.5%
4 4842
8.6%
ValueCountFrequency (%)
24 16
 
< 0.1%
23 32
 
0.1%
22 32
 
0.1%
21 83
0.1%
20 105
0.2%

Shots Total - home
Real number (ℝ)

ZEROS 

Distinct35
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.135763536
Minimum0
Maximum35
Zeros6497
Zeros (%)11.6%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:14.607098image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q39
95-th percentile15
Maximum35
Range35
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.953350213
Coefficient of variation (CV)0.8072915756
Kurtosis0.6384552859
Mean6.135763536
Median Absolute Deviation (MAD)3
Skewness0.8837343892
Sum344382
Variance24.53567833
MonotonicityNot monotonic
2025-01-04T15:12:14.755535image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 6497
11.6%
1 5002
 
8.9%
2 4501
 
8.0%
3 4488
 
8.0%
5 4156
 
7.4%
4 4094
 
7.3%
6 3954
 
7.0%
7 3798
 
6.8%
8 3390
 
6.0%
9 3232
 
5.8%
Other values (25) 13015
23.2%
ValueCountFrequency (%)
0 6497
11.6%
1 5002
8.9%
2 4501
8.0%
3 4488
8.0%
4 4094
7.3%
ValueCountFrequency (%)
35 1
 
< 0.1%
34 1
 
< 0.1%
33 5
< 0.1%
32 1
 
< 0.1%
31 3
< 0.1%

Substitutions - away
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.075257897
Minimum0
Maximum8
Zeros34436
Zeros (%)61.4%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:14.886263image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile5
Maximum8
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.643590015
Coefficient of variation (CV)1.528554237
Kurtosis0.5339073808
Mean1.075257897
Median Absolute Deviation (MAD)0
Skewness1.351955808
Sum60351
Variance2.701388138
MonotonicityNot monotonic
2025-01-04T15:12:15.013755image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 34436
61.4%
1 6091
 
10.9%
2 4137
 
7.4%
3 4122
 
7.3%
4 3503
 
6.2%
5 3494
 
6.2%
6 285
 
0.5%
7 44
 
0.1%
8 15
 
< 0.1%
ValueCountFrequency (%)
0 34436
61.4%
1 6091
 
10.9%
2 4137
 
7.4%
3 4122
 
7.3%
4 3503
 
6.2%
ValueCountFrequency (%)
8 15
 
< 0.1%
7 44
 
0.1%
6 285
 
0.5%
5 3494
6.2%
4 3503
6.2%

Substitutions - home
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.000160351
Minimum0
Maximum9
Zeros35474
Zeros (%)63.2%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:15.139467image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.58034983
Coefficient of variation (CV)1.580096461
Kurtosis0.8074834753
Mean1.000160351
Median Absolute Deviation (MAD)0
Skewness1.43339179
Sum56136
Variance2.497505587
MonotonicityNot monotonic
2025-01-04T15:12:15.255110image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 35474
63.2%
1 5806
 
10.3%
2 4269
 
7.6%
3 4105
 
7.3%
4 3144
 
5.6%
5 3123
 
5.6%
6 175
 
0.3%
7 17
 
< 0.1%
8 9
 
< 0.1%
9 5
 
< 0.1%
ValueCountFrequency (%)
0 35474
63.2%
1 5806
 
10.3%
2 4269
 
7.6%
3 4105
 
7.3%
4 3144
 
5.6%
ValueCountFrequency (%)
9 5
 
< 0.1%
8 9
 
< 0.1%
7 17
 
< 0.1%
6 175
 
0.3%
5 3123
5.6%

Successful Dribbles - away
Real number (ℝ)

ZEROS 

Distinct20
Distinct (%)< 0.1%
Missing6
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3.065590421
Minimum0
Maximum19
Zeros10187
Zeros (%)18.1%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:15.372849image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q35
95-th percentile9
Maximum19
Range19
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.839786948
Coefficient of variation (CV)0.9263425827
Kurtosis1.89096869
Mean3.065590421
Median Absolute Deviation (MAD)2
Skewness1.264414728
Sum172044
Variance8.064389908
MonotonicityNot monotonic
2025-01-04T15:12:15.509754image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 10262
18.3%
0 10187
18.1%
2 8812
15.7%
3 6723
12.0%
4 5933
10.6%
5 4011
 
7.1%
6 3531
 
6.3%
7 2106
 
3.8%
8 1509
 
2.7%
9 1102
 
2.0%
Other values (10) 1945
 
3.5%
ValueCountFrequency (%)
0 10187
18.1%
1 10262
18.3%
2 8812
15.7%
3 6723
12.0%
4 5933
10.6%
ValueCountFrequency (%)
19 19
 
< 0.1%
18 16
 
< 0.1%
17 23
 
< 0.1%
16 30
 
0.1%
15 100
0.2%

Successful Dribbles - home
Real number (ℝ)

ZEROS 

Distinct19
Distinct (%)< 0.1%
Missing6
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3.113023645
Minimum0
Maximum20
Zeros9851
Zeros (%)17.6%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:15.641804image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q35
95-th percentile9
Maximum20
Range20
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.839575259
Coefficient of variation (CV)0.9121598749
Kurtosis1.534954099
Mean3.113023645
Median Absolute Deviation (MAD)2
Skewness1.199835889
Sum174706
Variance8.063187652
MonotonicityNot monotonic
2025-01-04T15:12:15.774638image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1 10481
18.7%
0 9851
17.6%
2 8080
14.4%
3 7190
12.8%
4 5486
9.8%
5 4834
8.6%
6 3551
 
6.3%
7 2142
 
3.8%
8 1454
 
2.6%
9 1014
 
1.8%
Other values (9) 2038
 
3.6%
ValueCountFrequency (%)
0 9851
17.6%
1 10481
18.7%
2 8080
14.4%
3 7190
12.8%
4 5486
9.8%
ValueCountFrequency (%)
20 6
 
< 0.1%
17 18
 
< 0.1%
16 34
 
0.1%
15 47
 
0.1%
14 128
0.2%

Successful Headers - away
Real number (ℝ)

MISSING  ZEROS 

Distinct30
Distinct (%)0.1%
Missing4262
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean5.744104888
Minimum0
Maximum30
Zeros5087
Zeros (%)9.1%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:15.911150image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q38
95-th percentile15
Maximum30
Range30
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.814769971
Coefficient of variation (CV)0.8382106638
Kurtosis0.8685195047
Mean5.744104888
Median Absolute Deviation (MAD)3
Skewness1.038340472
Sum297918
Variance23.18200987
MonotonicityNot monotonic
2025-01-04T15:12:16.048306image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 5969
10.6%
2 5109
9.1%
0 5087
9.1%
3 4579
8.2%
4 4254
7.6%
5 4229
 
7.5%
6 3713
 
6.6%
7 3145
 
5.6%
8 2842
 
5.1%
9 2353
 
4.2%
Other values (20) 10585
18.9%
(Missing) 4262
7.6%
ValueCountFrequency (%)
0 5087
9.1%
1 5969
10.6%
2 5109
9.1%
3 4579
8.2%
4 4254
7.6%
ValueCountFrequency (%)
30 4
 
< 0.1%
28 11
< 0.1%
27 16
< 0.1%
26 13
< 0.1%
25 26
< 0.1%

Successful Headers - home
Real number (ℝ)

MISSING  ZEROS 

Distinct32
Distinct (%)0.1%
Missing4262
Missing (%)7.6%
Infinite0
Infinite (%)0.0%
Mean5.834628362
Minimum0
Maximum34
Zeros5236
Zeros (%)9.3%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:16.184812image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median5
Q39
95-th percentile15
Maximum34
Range34
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.956144643
Coefficient of variation (CV)0.849436217
Kurtosis0.9714152526
Mean5.834628362
Median Absolute Deviation (MAD)3
Skewness1.043110275
Sum302613
Variance24.56336973
MonotonicityNot monotonic
2025-01-04T15:12:16.327554image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 6341
11.3%
0 5236
9.3%
2 4821
8.6%
3 4789
8.5%
5 3856
 
6.9%
4 3726
 
6.6%
6 3507
 
6.2%
7 3079
 
5.5%
8 2833
 
5.0%
9 2470
 
4.4%
Other values (22) 11207
20.0%
(Missing) 4262
 
7.6%
ValueCountFrequency (%)
0 5236
9.3%
1 6341
11.3%
2 4821
8.6%
3 4789
8.5%
4 3726
6.6%
ValueCountFrequency (%)
34 3
 
< 0.1%
31 2
 
< 0.1%
30 6
 
< 0.1%
28 17
< 0.1%
27 24
< 0.1%

Successful Interceptions - away
Real number (ℝ)

ZEROS 

Distinct32
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.979154418
Minimum0
Maximum31
Zeros3730
Zeros (%)6.6%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:16.468446image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median6
Q310
95-th percentile17
Maximum31
Range31
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.149446043
Coefficient of variation (CV)0.7378323697
Kurtosis0.1573337208
Mean6.979154418
Median Absolute Deviation (MAD)4
Skewness0.7485351739
Sum391719
Variance26.51679455
MonotonicityNot monotonic
2025-01-04T15:12:16.603912image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 4660
 
8.3%
2 4494
 
8.0%
5 4330
 
7.7%
4 4257
 
7.6%
3 4142
 
7.4%
6 3784
 
6.7%
7 3771
 
6.7%
0 3730
 
6.6%
9 3471
 
6.2%
8 3250
 
5.8%
Other values (22) 16238
28.9%
ValueCountFrequency (%)
0 3730
6.6%
1 4660
8.3%
2 4494
8.0%
3 4142
7.4%
4 4257
7.6%
ValueCountFrequency (%)
31 3
 
< 0.1%
30 2
 
< 0.1%
29 15
< 0.1%
28 13
< 0.1%
27 12
< 0.1%

Successful Interceptions - home
Real number (ℝ)

ZEROS 

Distinct31
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.089012418
Minimum0
Maximum30
Zeros3843
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:16.739713image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median6
Q311
95-th percentile17
Maximum30
Range30
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.251592126
Coefficient of variation (CV)0.7408072968
Kurtosis0.05675350085
Mean7.089012418
Median Absolute Deviation (MAD)4
Skewness0.721466885
Sum397885
Variance27.57921986
MonotonicityNot monotonic
2025-01-04T15:12:16.872653image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 4710
 
8.4%
2 4354
 
7.8%
4 4350
 
7.8%
3 4123
 
7.3%
5 4030
 
7.2%
0 3843
 
6.8%
8 3708
 
6.6%
7 3654
 
6.5%
6 3237
 
5.8%
9 3182
 
5.7%
Other values (21) 16936
30.2%
ValueCountFrequency (%)
0 3843
6.8%
1 4710
8.4%
2 4354
7.8%
3 4123
7.3%
4 4350
7.8%
ValueCountFrequency (%)
30 10
< 0.1%
29 14
< 0.1%
28 10
< 0.1%
27 15
< 0.1%
26 17
< 0.1%

Successful Passes - away
Real number (ℝ)

ZEROS 

Distinct645
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean171.937392
Minimum0
Maximum765
Zeros602
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:17.022030image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12
Q176
median154
Q3248
95-th percentile397
Maximum765
Range765
Interquartile range (IQR)172

Descriptive statistics

Standard deviation120.7210291
Coefficient of variation (CV)0.7021220207
Kurtosis0.4800276252
Mean171.937392
Median Absolute Deviation (MAD)85
Skewness0.7968207592
Sum9650330
Variance14573.56687
MonotonicityNot monotonic
2025-01-04T15:12:17.189442image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 602
 
1.1%
1 386
 
0.7%
106 261
 
0.5%
3 244
 
0.4%
2 238
 
0.4%
112 225
 
0.4%
147 223
 
0.4%
115 222
 
0.4%
88 217
 
0.4%
89 214
 
0.4%
Other values (635) 53295
95.0%
ValueCountFrequency (%)
0 602
1.1%
1 386
0.7%
2 238
 
0.4%
3 244
0.4%
4 140
 
0.2%
ValueCountFrequency (%)
765 1
 
< 0.1%
762 1
 
< 0.1%
758 4
< 0.1%
756 2
< 0.1%
740 3
< 0.1%

Successful Passes - home
Real number (ℝ)

ZEROS 

Distinct636
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean178.7746539
Minimum0
Maximum724
Zeros645
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:17.352106image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13
Q181
median162
Q3258
95-th percentile404
Maximum724
Range724
Interquartile range (IQR)177

Descriptive statistics

Standard deviation122.4352989
Coefficient of variation (CV)0.6848582627
Kurtosis0.1007830156
Mean178.7746539
Median Absolute Deviation (MAD)88
Skewness0.6859577379
Sum10034085
Variance14990.40241
MonotonicityNot monotonic
2025-01-04T15:12:17.516522image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 645
 
1.1%
1 293
 
0.5%
2 220
 
0.4%
155 218
 
0.4%
97 212
 
0.4%
43 211
 
0.4%
135 209
 
0.4%
102 208
 
0.4%
114 207
 
0.4%
176 206
 
0.4%
Other values (626) 53498
95.3%
ValueCountFrequency (%)
0 645
1.1%
1 293
0.5%
2 220
 
0.4%
3 173
 
0.3%
4 143
 
0.3%
ValueCountFrequency (%)
724 2
< 0.1%
709 3
< 0.1%
702 4
< 0.1%
700 2
< 0.1%
692 1
 
< 0.1%
Distinct72
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79.27537549
Minimum0
Maximum100
Zeros560
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:17.685793image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile63
Q176
median81
Q386
95-th percentile91
Maximum100
Range100
Interquartile range (IQR)10

Descriptive statistics

Standard deviation11.797946
Coefficient of variation (CV)0.1488223288
Kurtosis19.33986962
Mean79.27537549
Median Absolute Deviation (MAD)5
Skewness-3.446918775
Sum4449489
Variance139.1915297
MonotonicityNot monotonic
2025-01-04T15:12:17.846573image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84 3324
 
5.9%
85 3208
 
5.7%
81 2949
 
5.3%
80 2851
 
5.1%
82 2845
 
5.1%
83 2783
 
5.0%
78 2630
 
4.7%
79 2556
 
4.6%
86 2496
 
4.4%
88 2430
 
4.3%
Other values (62) 28055
50.0%
ValueCountFrequency (%)
0 560
1.0%
16 13
 
< 0.1%
20 3
 
< 0.1%
25 35
 
0.1%
27 2
 
< 0.1%
ValueCountFrequency (%)
100 467
0.8%
98 6
 
< 0.1%
97 33
 
0.1%
96 52
 
0.1%
95 98
 
0.2%

Successful Passes Percentage - home
Real number (ℝ)

ZEROS 

Distinct73
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80.31568586
Minimum0
Maximum100
Zeros637
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:18.216500image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile66
Q177
median82
Q387
95-th percentile91
Maximum100
Range100
Interquartile range (IQR)10

Descriptive statistics

Standard deviation11.75822776
Coefficient of variation (CV)0.1464001413
Kurtosis23.31880989
Mean80.31568586
Median Absolute Deviation (MAD)5
Skewness-3.952980497
Sum4507878.5
Variance138.2559201
MonotonicityNot monotonic
2025-01-04T15:12:18.378148image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
85 3521
 
6.3%
84 3403
 
6.1%
86 3354
 
6.0%
87 3188
 
5.7%
83 3024
 
5.4%
88 2871
 
5.1%
82 2816
 
5.0%
80 2806
 
5.0%
81 2767
 
4.9%
89 2492
 
4.4%
Other values (63) 25885
46.1%
ValueCountFrequency (%)
0 637
1.1%
7 2
 
< 0.1%
12 1
 
< 0.1%
16 4
 
< 0.1%
17 1
 
< 0.1%
ValueCountFrequency (%)
100 445
0.8%
97 17
 
< 0.1%
96 34
 
0.1%
95 94
 
0.2%
94 219
0.4%

Tackles - away
Real number (ℝ)

ZEROS 

Distinct33
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.675860103
Minimum0
Maximum32
Zeros3493
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:18.523149image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median7
Q311
95-th percentile18
Maximum32
Range32
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.550842326
Coefficient of variation (CV)0.7231557443
Kurtosis-0.08540278805
Mean7.675860103
Median Absolute Deviation (MAD)4
Skewness0.6560859135
Sum430823
Variance30.81185053
MonotonicityNot monotonic
2025-01-04T15:12:18.660420image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1 4334
 
7.7%
2 3924
 
7.0%
5 3864
 
6.9%
3 3802
 
6.8%
4 3770
 
6.7%
6 3696
 
6.6%
7 3514
 
6.3%
0 3493
 
6.2%
9 3230
 
5.8%
8 3054
 
5.4%
Other values (23) 19446
34.6%
ValueCountFrequency (%)
0 3493
6.2%
1 4334
7.7%
2 3924
7.0%
3 3802
6.8%
4 3770
6.7%
ValueCountFrequency (%)
32 2
 
< 0.1%
31 6
 
< 0.1%
30 8
 
< 0.1%
29 29
0.1%
28 24
< 0.1%

Tackles - home
Real number (ℝ)

ZEROS 

Distinct33
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.902471181
Minimum0
Maximum32
Zeros3513
Zeros (%)6.3%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:18.799813image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median7
Q312
95-th percentile18
Maximum32
Range32
Interquartile range (IQR)9

Descriptive statistics

Standard deviation5.612773571
Coefficient of variation (CV)0.7102554937
Kurtosis-0.1906652192
Mean7.902471181
Median Absolute Deviation (MAD)4
Skewness0.5985077646
Sum443542
Variance31.50322715
MonotonicityNot monotonic
2025-01-04T15:12:18.937284image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
1 4048
 
7.2%
4 3830
 
6.8%
2 3726
 
6.6%
5 3634
 
6.5%
3 3521
 
6.3%
0 3513
 
6.3%
6 3439
 
6.1%
8 3439
 
6.1%
7 3334
 
5.9%
9 3133
 
5.6%
Other values (23) 20510
36.5%
ValueCountFrequency (%)
0 3513
6.3%
1 4048
7.2%
2 3726
6.6%
3 3521
6.3%
4 3830
6.8%
ValueCountFrequency (%)
32 2
 
< 0.1%
31 6
 
< 0.1%
30 9
< 0.1%
29 22
< 0.1%
28 13
< 0.1%

Throwins - away
Real number (ℝ)

ZEROS 

Distinct35
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.212856557
Minimum0
Maximum34
Zeros3394
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:19.076076image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median7
Q312
95-th percentile19
Maximum34
Range34
Interquartile range (IQR)9

Descriptive statistics

Standard deviation5.871629766
Coefficient of variation (CV)0.7149314888
Kurtosis-0.03996438034
Mean8.212856557
Median Absolute Deviation (MAD)4
Skewness0.6469059005
Sum460963
Variance34.47603611
MonotonicityNot monotonic
2025-01-04T15:12:19.217932image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1 4081
 
7.3%
2 3633
 
6.5%
5 3507
 
6.2%
7 3449
 
6.1%
4 3436
 
6.1%
6 3405
 
6.1%
0 3394
 
6.0%
8 3359
 
6.0%
9 3326
 
5.9%
3 3246
 
5.8%
Other values (25) 21291
37.9%
ValueCountFrequency (%)
0 3394
6.0%
1 4081
7.3%
2 3633
6.5%
3 3246
5.8%
4 3436
6.1%
ValueCountFrequency (%)
34 1
 
< 0.1%
33 3
 
< 0.1%
32 21
< 0.1%
31 24
< 0.1%
30 14
< 0.1%

Throwins - home
Real number (ℝ)

ZEROS 

Distinct44
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.492454612
Minimum0
Maximum45
Zeros2862
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:19.369921image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median8
Q312
95-th percentile20
Maximum45
Range45
Interquartile range (IQR)9

Descriptive statistics

Standard deviation6.225258987
Coefficient of variation (CV)0.7330341193
Kurtosis0.4591257001
Mean8.492454612
Median Absolute Deviation (MAD)5
Skewness0.8015023243
Sum476656
Variance38.75384946
MonotonicityNot monotonic
2025-01-04T15:12:19.522929image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1 4079
 
7.3%
2 3860
 
6.9%
4 3544
 
6.3%
3 3533
 
6.3%
5 3523
 
6.3%
6 3308
 
5.9%
7 3188
 
5.7%
9 3149
 
5.6%
8 3083
 
5.5%
10 2899
 
5.2%
Other values (34) 21961
39.1%
ValueCountFrequency (%)
0 2862
5.1%
1 4079
7.3%
2 3860
6.9%
3 3533
6.3%
4 3544
6.3%
ValueCountFrequency (%)
45 3
< 0.1%
44 3
< 0.1%
43 1
 
< 0.1%
40 4
< 0.1%
39 3
< 0.1%

Total Crosses - away
Real number (ℝ)

ZEROS 

Distinct40
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.141411442
Minimum0
Maximum44
Zeros5430
Zeros (%)9.7%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:19.679098image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median6
Q311
95-th percentile19
Maximum44
Range44
Interquartile range (IQR)9

Descriptive statistics

Standard deviation5.959069159
Coefficient of variation (CV)0.8344385711
Kurtosis1.085837008
Mean7.141411442
Median Absolute Deviation (MAD)4
Skewness1.047071767
Sum400826
Variance35.51050525
MonotonicityNot monotonic
2025-01-04T15:12:19.828689image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0 5430
 
9.7%
1 4880
 
8.7%
2 4555
 
8.1%
3 4070
 
7.3%
4 3895
 
6.9%
6 3810
 
6.8%
5 3581
 
6.4%
7 3085
 
5.5%
8 3030
 
5.4%
10 2751
 
4.9%
Other values (30) 17040
30.4%
ValueCountFrequency (%)
0 5430
9.7%
1 4880
8.7%
2 4555
8.1%
3 4070
7.3%
4 3895
6.9%
ValueCountFrequency (%)
44 1
 
< 0.1%
40 3
 
< 0.1%
38 4
 
< 0.1%
37 5
 
< 0.1%
35 14
< 0.1%

Total Crosses - home
Real number (ℝ)

ZEROS 

Distinct45
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.022841057
Minimum0
Maximum44
Zeros4129
Zeros (%)7.4%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:19.977397image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median8
Q313
95-th percentile23
Maximum44
Range44
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.190807061
Coefficient of variation (CV)0.7969559716
Kurtosis0.6386117014
Mean9.022841057
Median Absolute Deviation (MAD)5
Skewness0.9196395555
Sum506425
Variance51.70770619
MonotonicityNot monotonic
2025-01-04T15:12:20.124091image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
1 4200
 
7.5%
0 4129
 
7.4%
2 3443
 
6.1%
3 3371
 
6.0%
4 3279
 
5.8%
5 3109
 
5.5%
6 3094
 
5.5%
8 2896
 
5.2%
7 2889
 
5.1%
9 2846
 
5.1%
Other values (35) 22871
40.7%
ValueCountFrequency (%)
0 4129
7.4%
1 4200
7.5%
2 3443
6.1%
3 3371
6.0%
4 3279
5.8%
ValueCountFrequency (%)
44 2
 
< 0.1%
43 17
< 0.1%
42 16
< 0.1%
41 10
< 0.1%
40 13
< 0.1%

Yellowcards - away
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8401126018
Minimum0
Maximum8
Zeros28723
Zeros (%)51.2%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:20.245572image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum8
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.114248108
Coefficient of variation (CV)1.326308051
Kurtosis3.681993239
Mean0.8401126018
Median Absolute Deviation (MAD)0
Skewness1.668613692
Sum47153
Variance1.241548845
MonotonicityNot monotonic
2025-01-04T15:12:20.375005image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 28723
51.2%
1 15010
26.7%
2 7576
 
13.5%
3 3184
 
5.7%
4 1077
 
1.9%
5 346
 
0.6%
6 123
 
0.2%
8 47
 
0.1%
7 41
 
0.1%
ValueCountFrequency (%)
0 28723
51.2%
1 15010
26.7%
2 7576
 
13.5%
3 3184
 
5.7%
4 1077
 
1.9%
ValueCountFrequency (%)
8 47
 
0.1%
7 41
 
0.1%
6 123
 
0.2%
5 346
 
0.6%
4 1077
1.9%

Yellowcards - home
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7478040872
Minimum0
Maximum6
Zeros30840
Zeros (%)54.9%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:20.496743image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.028971057
Coefficient of variation (CV)1.375990148
Kurtosis2.109898184
Mean0.7478040872
Median Absolute Deviation (MAD)0
Skewness1.511297043
Sum41972
Variance1.058781436
MonotonicityNot monotonic
2025-01-04T15:12:20.609335image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 30840
54.9%
1 14330
25.5%
2 6886
 
12.3%
3 2739
 
4.9%
4 1032
 
1.8%
5 275
 
0.5%
6 25
 
< 0.1%
ValueCountFrequency (%)
0 30840
54.9%
1 14330
25.5%
2 6886
 
12.3%
3 2739
 
4.9%
4 1032
 
1.8%
ValueCountFrequency (%)
6 25
 
< 0.1%
5 275
 
0.5%
4 1032
 
1.8%
3 2739
 
4.9%
2 6886
12.3%

Yellowred Cards - away
Real number (ℝ)

MISSING  ZEROS 

Distinct3
Distinct (%)< 0.1%
Missing7128
Missing (%)12.7%
Infinite0
Infinite (%)0.0%
Mean0.009000183677
Minimum0
Maximum2
Zeros48597
Zeros (%)86.6%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:20.723601image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum2
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1025244562
Coefficient of variation (CV)11.39137376
Kurtosis174.896979
Mean0.009000183677
Median Absolute Deviation (MAD)0
Skewness12.51977778
Sum441
Variance0.01051126411
MonotonicityNot monotonic
2025-01-04T15:12:20.842161image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
0 48597
86.6%
1 363
 
0.6%
2 39
 
0.1%
(Missing) 7128
 
12.7%
ValueCountFrequency (%)
0 48597
86.6%
1 363
 
0.6%
2 39
 
0.1%
ValueCountFrequency (%)
2 39
 
0.1%
1 363
 
0.6%
0 48597
86.6%

Yellowred Cards - home
Real number (ℝ)

MISSING  ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing7128
Missing (%)12.7%
Infinite0
Infinite (%)0.0%
Mean0.004816424825
Minimum0
Maximum1
Zeros48763
Zeros (%)86.9%
Negative0
Negative (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:20.964241image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.06923384073
Coefficient of variation (CV)14.3745295
Kurtosis202.6485218
Mean0.004816424825
Median Absolute Deviation (MAD)0
Skewness14.30525254
Sum236
Variance0.004793324702
MonotonicityNot monotonic
2025-01-04T15:12:21.077764image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 48763
86.9%
1 236
 
0.4%
(Missing) 7128
 
12.7%
ValueCountFrequency (%)
0 48763
86.9%
1 236
 
0.4%
ValueCountFrequency (%)
1 236
 
0.4%
0 48763
86.9%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:21.152802image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters56127
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowX
2nd rowX
3rd rowX
4th rowX
5th rowX
ValueCountFrequency (%)
x 27868
49.7%
1 15637
27.9%
2 12622
22.5%
2025-01-04T15:12:21.362354image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
X 27868
49.7%
1 15637
27.9%
2 12622
22.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 56127
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
X 27868
49.7%
1 15637
27.9%
2 12622
22.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 56127
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
X 27868
49.7%
1 15637
27.9%
2 12622
22.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 56127
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
X 27868
49.7%
1 15637
27.9%
2 12622
22.5%
Distinct39
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:21.518643image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters168381
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1-0
2nd row1-0
3rd row1-0
4th row1-0
5th row1-0
ValueCountFrequency (%)
1-1 7204
12.8%
2-1 5601
 
10.0%
1-0 4879
 
8.7%
0-0 4466
 
8.0%
0-1 3642
 
6.5%
1-2 3376
 
6.0%
2-0 3308
 
5.9%
2-2 3187
 
5.7%
3-1 3153
 
5.6%
0-2 3066
 
5.5%
Other values (29) 14245
25.4%
2025-01-04T15:12:21.801022image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 56127
33.3%
1 37981
22.6%
0 28423
16.9%
2 27159
16.1%
3 13421
 
8.0%
4 3961
 
2.4%
5 939
 
0.6%
6 240
 
0.1%
7 108
 
0.1%
8 22
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 168381
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
- 56127
33.3%
1 37981
22.6%
0 28423
16.9%
2 27159
16.1%
3 13421
 
8.0%
4 3961
 
2.4%
5 939
 
0.6%
6 240
 
0.1%
7 108
 
0.1%
8 22
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 168381
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
- 56127
33.3%
1 37981
22.6%
0 28423
16.9%
2 27159
16.1%
3 13421
 
8.0%
4 3961
 
2.4%
5 939
 
0.6%
6 240
 
0.1%
7 108
 
0.1%
8 22
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 168381
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
- 56127
33.3%
1 37981
22.6%
0 28423
16.9%
2 27159
16.1%
3 13421
 
8.0%
4 3961
 
2.4%
5 939
 
0.6%
6 240
 
0.1%
7 108
 
0.1%
8 22
 
< 0.1%

result
Text

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size438.6 KiB
2025-01-04T15:12:21.895591image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters56127
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 24148
43.0%
2 16588
29.6%
x 15391
27.4%
2025-01-04T15:12:22.102421image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 24148
43.0%
2 16588
29.6%
X 15391
27.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 56127
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 24148
43.0%
2 16588
29.6%
X 15391
27.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 56127
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 24148
43.0%
2 16588
29.6%
X 15391
27.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 56127
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 24148
43.0%
2 16588
29.6%
X 15391
27.4%